galleri5
/
alien-green
Trained on generations with this melting green aesthetic cultivated using Stable Diffusion 2.1 ( Realism Engine) with themes from Aliens, Bollywood, Surrealism among many. WIP. Refer to Examples for trigger words
- Public
- 395 runs
-
L40S
- SDXL fine-tune
Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beIDhd4snldbvvwpx5dcsxee6g34jyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARAP, a young woman with brightly colored hair
- refine
- no_refiner
- scheduler
- K_EULER_ANCESTRAL
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAP, a young woman with brightly colored hair", "refine": "no_refiner", "scheduler": "K_EULER_ANCESTRAL", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARAP, a young woman with brightly colored hair", refine: "no_refiner", scheduler: "K_EULER_ANCESTRAL", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAP, a young woman with brightly colored hair", "refine": "no_refiner", "scheduler": "K_EULER_ANCESTRAL", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAP, a young woman with brightly colored hair", "refine": "no_refiner", "scheduler": "K_EULER_ANCESTRAL", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T18:42:39.199288Z", "created_at": "2023-09-27T18:42:23.600462Z", "data_removed": false, "error": null, "id": "hd4snldbvvwpx5dcsxee6g34jy", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAP, a young woman with brightly colored hair", "refine": "no_refiner", "scheduler": "K_EULER_ANCESTRAL", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 46816\nPrompt: In the style of GRINTHARAP, a young woman with brightly colored hair\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.71it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.70it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.70it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.70it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.71it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.71it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.71it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.71it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.71it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.71it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.71it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.71it/s]\n 26%|██▌ | 13/50 [00:03<00:09, 3.71it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.71it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.71it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.70it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.70it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.70it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.70it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.70it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.70it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.70it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.70it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.70it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.69it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.69it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.70it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.70it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.69it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.69it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.69it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.69it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.69it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.69it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.69it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.69it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.69it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.69it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.69it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.69it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.69it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.69it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.70it/s]", "metrics": { "predict_time": 15.636197, "total_time": 15.598826 }, "output": [ "https://pbxt.replicate.delivery/EKLpZFKASjqNLl0dnFxRF3eveBZmor3FCmcneSNZSpL9MFRjA/out-0.png" ], "started_at": "2023-09-27T18:42:23.563091Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hd4snldbvvwpx5dcsxee6g34jy", "cancel": "https://api.replicate.com/v1/predictions/hd4snldbvvwpx5dcsxee6g34jy/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 46816 Prompt: In the style of GRINTHARAP, a young woman with brightly colored hair txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.71it/s] 4%|▍ | 2/50 [00:00<00:12, 3.70it/s] 6%|▌ | 3/50 [00:00<00:12, 3.70it/s] 8%|▊ | 4/50 [00:01<00:12, 3.70it/s] 10%|█ | 5/50 [00:01<00:12, 3.71it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.71it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.71it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.71it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.71it/s] 20%|██ | 10/50 [00:02<00:10, 3.71it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.71it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.71it/s] 26%|██▌ | 13/50 [00:03<00:09, 3.71it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.71it/s] 30%|███ | 15/50 [00:04<00:09, 3.71it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.70it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.70it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.70it/s] 40%|████ | 20/50 [00:05<00:08, 3.70it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.70it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.70it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.70it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.70it/s] 50%|█████ | 25/50 [00:06<00:06, 3.70it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.69it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.69it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.70it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.70it/s] 60%|██████ | 30/50 [00:08<00:05, 3.69it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.69it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.69it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.69it/s] 70%|███████ | 35/50 [00:09<00:04, 3.69it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.69it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.69it/s] 80%|████████ | 40/50 [00:10<00:02, 3.69it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.69it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.69it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.69it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.69it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.69it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.69it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.69it/s] 100%|██████████| 50/50 [00:13<00:00, 3.69it/s] 100%|██████████| 50/50 [00:13<00:00, 3.70it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beID72jogpdbwikklt2fxg7axknyk4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARAPE, reverse split cotton meat
- refine
- no_refiner
- scheduler
- DDIM
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton meat", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARAPE, reverse split cotton meat", refine: "no_refiner", scheduler: "DDIM", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton meat", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton meat", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T18:54:39.791318Z", "created_at": "2023-09-27T18:54:24.149204Z", "data_removed": false, "error": null, "id": "72jogpdbwikklt2fxg7axknyk4", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton meat", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 6546\nPrompt: In the style of GRINTHARAPE, reverse split cotton meat\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.71it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.69it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.69it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.69it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.69it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.68it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.70it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.70it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.70it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.70it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.70it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.70it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.70it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.70it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.70it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.70it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.70it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.70it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.70it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.70it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.70it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.70it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.70it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.70it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.70it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.69it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.69it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.69it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.69it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.68it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.69it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.69it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.69it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.68it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.69it/s]", "metrics": { "predict_time": 15.635005, "total_time": 15.642114 }, "output": [ "https://pbxt.replicate.delivery/eyoIYgXIVmwSfU3TtOn5qGKZ3BZ74v7Ph7NnEE2vBI4uxioRA/out-0.png" ], "started_at": "2023-09-27T18:54:24.156313Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/72jogpdbwikklt2fxg7axknyk4", "cancel": "https://api.replicate.com/v1/predictions/72jogpdbwikklt2fxg7axknyk4/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 6546 Prompt: In the style of GRINTHARAPE, reverse split cotton meat txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.71it/s] 4%|▍ | 2/50 [00:00<00:12, 3.69it/s] 6%|▌ | 3/50 [00:00<00:12, 3.69it/s] 8%|▊ | 4/50 [00:01<00:12, 3.69it/s] 10%|█ | 5/50 [00:01<00:12, 3.69it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.68it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s] 20%|██ | 10/50 [00:02<00:10, 3.70it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.70it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.70it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.70it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.70it/s] 30%|███ | 15/50 [00:04<00:09, 3.70it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.70it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.70it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.70it/s] 40%|████ | 20/50 [00:05<00:08, 3.70it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.70it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.70it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s] 50%|█████ | 25/50 [00:06<00:06, 3.70it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.70it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.70it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.70it/s] 60%|██████ | 30/50 [00:08<00:05, 3.70it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.70it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.70it/s] 70%|███████ | 35/50 [00:09<00:04, 3.69it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.69it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.69it/s] 80%|████████ | 40/50 [00:10<00:02, 3.69it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.68it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.69it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.69it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.69it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.68it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.69it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beIDvzr4snlbtxz3nux5d5naaa2mzmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARAPE, tree murder
- refine
- no_refiner
- scheduler
- DDIM
- lora_scale
- 1
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.73
- negative_prompt
- realistic, blurry
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, tree murder", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.73, "negative_prompt": "realistic, blurry", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARAPE, tree murder", refine: "no_refiner", scheduler: "DDIM", lora_scale: 1, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.73, negative_prompt: "realistic, blurry", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, tree murder", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.73, "negative_prompt": "realistic, blurry", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, tree murder", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.73, "negative_prompt": "realistic, blurry", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T19:05:28.784450Z", "created_at": "2023-09-27T19:05:12.753182Z", "data_removed": false, "error": null, "id": "vzr4snlbtxz3nux5d5naaa2mzm", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, tree murder", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.73, "negative_prompt": "realistic, blurry", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 55240\nPrompt: In the style of GRINTHARAPE, tree murder\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.72it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.71it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.70it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.70it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.70it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.70it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.69it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.69it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.68it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.68it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.68it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.68it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.68it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.68it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.68it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.68it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.68it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.68it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.68it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.68it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.68it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.68it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.68it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.68it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.68it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.68it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.68it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.67it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]", "metrics": { "predict_time": 15.975525, "total_time": 16.031268 }, "output": [ "https://pbxt.replicate.delivery/neQ1gCu43mUUZ6VHZm9T9UswtykqqpKy8zTfyNeUwrvv3FRjA/out-0.png" ], "started_at": "2023-09-27T19:05:12.808925Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vzr4snlbtxz3nux5d5naaa2mzm", "cancel": "https://api.replicate.com/v1/predictions/vzr4snlbtxz3nux5d5naaa2mzm/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 55240 Prompt: In the style of GRINTHARAPE, tree murder txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.72it/s] 4%|▍ | 2/50 [00:00<00:12, 3.71it/s] 6%|▌ | 3/50 [00:00<00:12, 3.70it/s] 8%|▊ | 4/50 [00:01<00:12, 3.70it/s] 10%|█ | 5/50 [00:01<00:12, 3.70it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.70it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s] 20%|██ | 10/50 [00:02<00:10, 3.69it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.69it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s] 30%|███ | 15/50 [00:04<00:09, 3.68it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.68it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.68it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s] 40%|████ | 20/50 [00:05<00:08, 3.68it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.68it/s] 50%|█████ | 25/50 [00:06<00:06, 3.68it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.68it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.68it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.68it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s] 60%|██████ | 30/50 [00:08<00:05, 3.68it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.68it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.68it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s] 70%|███████ | 35/50 [00:09<00:04, 3.68it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.68it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.68it/s] 80%|████████ | 40/50 [00:10<00:02, 3.68it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.68it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.68it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.68it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.67it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.68it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beIDvd6agllbio3f7pxdsmxckohbyeStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARAPE, reverse split cotton meat juice
- refine
- no_refiner
- scheduler
- DDIM
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton meat juice", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARAPE, reverse split cotton meat juice", refine: "no_refiner", scheduler: "DDIM", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton meat juice", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton meat juice", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T19:52:07.405490Z", "created_at": "2023-09-27T19:51:37.890070Z", "data_removed": false, "error": null, "id": "vd6agllbio3f7pxdsmxckohbye", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton meat juice", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 40908\nPrompt: In the style of GRINTHARAPE, reverse split cotton meat juice\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.70it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.71it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.71it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.70it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.70it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.70it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.70it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.70it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.70it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.70it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.70it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.70it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.70it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.70it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.70it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.69it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.69it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.69it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.69it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.69it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.69it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.69it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.69it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.69it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.69it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.69it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.69it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.69it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.68it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.69it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.68it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.68it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.68it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.68it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.68it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.68it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.68it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.68it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.69it/s]", "metrics": { "predict_time": 15.958814, "total_time": 29.51542 }, "output": [ "https://pbxt.replicate.delivery/4PT7ExR8RvpEKpJNBQvbkCF8F67gCFVewzDTWrwjBqAzzR0IA/out-0.png" ], "started_at": "2023-09-27T19:51:51.446676Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vd6agllbio3f7pxdsmxckohbye", "cancel": "https://api.replicate.com/v1/predictions/vd6agllbio3f7pxdsmxckohbye/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 40908 Prompt: In the style of GRINTHARAPE, reverse split cotton meat juice txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.70it/s] 4%|▍ | 2/50 [00:00<00:12, 3.71it/s] 6%|▌ | 3/50 [00:00<00:12, 3.71it/s] 8%|▊ | 4/50 [00:01<00:12, 3.70it/s] 10%|█ | 5/50 [00:01<00:12, 3.70it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.70it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.70it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.70it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.70it/s] 20%|██ | 10/50 [00:02<00:10, 3.70it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.70it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.70it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.70it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.70it/s] 30%|███ | 15/50 [00:04<00:09, 3.70it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.69it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.69it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.69it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.69it/s] 40%|████ | 20/50 [00:05<00:08, 3.69it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.69it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.69it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s] 50%|█████ | 25/50 [00:06<00:06, 3.69it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.69it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.69it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.69it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.69it/s] 60%|██████ | 30/50 [00:08<00:05, 3.69it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.68it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.69it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s] 70%|███████ | 35/50 [00:09<00:04, 3.68it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.68it/s] 80%|████████ | 40/50 [00:10<00:02, 3.68it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.68it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.68it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.68it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.68it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.68it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.69it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beIDtbapo5dbsib527k7qzkjtd3lrqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARAPE, onion crow hybrid
- refine
- no_refiner
- scheduler
- DDIM
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, onion crow hybrid", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARAPE, onion crow hybrid", refine: "no_refiner", scheduler: "DDIM", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, onion crow hybrid", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, onion crow hybrid", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T20:03:53.760959Z", "created_at": "2023-09-27T20:03:37.789117Z", "data_removed": false, "error": null, "id": "tbapo5dbsib527k7qzkjtd3lrq", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, onion crow hybrid", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 37279\nPrompt: In the style of GRINTHARAPE, onion crow hybrid\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.71it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.71it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.70it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.69it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.69it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.68it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.68it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.68it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.68it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.68it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.68it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.68it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.68it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.68it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.67it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.67it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.68it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.68it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.67it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.68it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.67it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.67it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.67it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.67it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.67it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.67it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.67it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.67it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.67it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.67it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]", "metrics": { "predict_time": 15.973583, "total_time": 15.971842 }, "output": [ "https://pbxt.replicate.delivery/vaKUfqd6ven5QEe5k6kDAOogwp43hkhEpsYLrdr2ciIQlHRjA/out-0.png" ], "started_at": "2023-09-27T20:03:37.787376Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tbapo5dbsib527k7qzkjtd3lrq", "cancel": "https://api.replicate.com/v1/predictions/tbapo5dbsib527k7qzkjtd3lrq/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 37279 Prompt: In the style of GRINTHARAPE, onion crow hybrid txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.71it/s] 4%|▍ | 2/50 [00:00<00:12, 3.71it/s] 6%|▌ | 3/50 [00:00<00:12, 3.70it/s] 8%|▊ | 4/50 [00:01<00:12, 3.69it/s] 10%|█ | 5/50 [00:01<00:12, 3.69it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.68it/s] 20%|██ | 10/50 [00:02<00:10, 3.68it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s] 30%|███ | 15/50 [00:04<00:09, 3.68it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.68it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.68it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s] 40%|████ | 20/50 [00:05<00:08, 3.68it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.68it/s] 50%|█████ | 25/50 [00:06<00:06, 3.68it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.68it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.67it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.67it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s] 60%|██████ | 30/50 [00:08<00:05, 3.68it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.68it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.67it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s] 70%|███████ | 35/50 [00:09<00:04, 3.68it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.67it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.67it/s] 80%|████████ | 40/50 [00:10<00:02, 3.67it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.67it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.67it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.67it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.67it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.67it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.67it/s] 100%|██████████| 50/50 [00:13<00:00, 3.67it/s] 100%|██████████| 50/50 [00:13<00:00, 3.68it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beIDxwh2bmtbso6xmyzs3pz3nvsbwmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARA, onion crow bubblegum flower juice
- refine
- no_refiner
- scheduler
- K_EULER_ANCESTRAL
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARA, onion crow bubblegum flower juice", "refine": "no_refiner", "scheduler": "K_EULER_ANCESTRAL", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARA, onion crow bubblegum flower juice", refine: "no_refiner", scheduler: "K_EULER_ANCESTRAL", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARA, onion crow bubblegum flower juice", "refine": "no_refiner", "scheduler": "K_EULER_ANCESTRAL", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARA, onion crow bubblegum flower juice", "refine": "no_refiner", "scheduler": "K_EULER_ANCESTRAL", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T20:15:27.608356Z", "created_at": "2023-09-27T20:15:11.709369Z", "data_removed": false, "error": null, "id": "xwh2bmtbso6xmyzs3pz3nvsbwm", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARA, onion crow bubblegum flower juice", "refine": "no_refiner", "scheduler": "K_EULER_ANCESTRAL", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 18872\nPrompt: In the style of GRINTHARA, onion crow bubblegum flower juice\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.71it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.71it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.70it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.70it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.69it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.68it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.69it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.69it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.69it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.70it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.70it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.70it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.70it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.71it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.70it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.70it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.70it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.70it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.70it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.70it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.70it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.70it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.70it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.70it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.70it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.70it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.70it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.70it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.70it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.70it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.70it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.70it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.70it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.69it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.70it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.70it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.70it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.70it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.70it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.70it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.70it/s]", "metrics": { "predict_time": 15.908707, "total_time": 15.898987 }, "output": [ "https://pbxt.replicate.delivery/XMDtBvHqQIZtO1VC5BaHX6A77cV1QaFePJSuinZ9FzDvejoRA/out-0.png" ], "started_at": "2023-09-27T20:15:11.699649Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xwh2bmtbso6xmyzs3pz3nvsbwm", "cancel": "https://api.replicate.com/v1/predictions/xwh2bmtbso6xmyzs3pz3nvsbwm/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 18872 Prompt: In the style of GRINTHARA, onion crow bubblegum flower juice txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.71it/s] 4%|▍ | 2/50 [00:00<00:12, 3.71it/s] 6%|▌ | 3/50 [00:00<00:12, 3.70it/s] 8%|▊ | 4/50 [00:01<00:12, 3.70it/s] 10%|█ | 5/50 [00:01<00:12, 3.69it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s] 20%|██ | 10/50 [00:02<00:10, 3.68it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.69it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.69it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.69it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.70it/s] 30%|███ | 15/50 [00:04<00:09, 3.70it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.70it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.70it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.71it/s] 40%|████ | 20/50 [00:05<00:08, 3.70it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.70it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.70it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.70it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.70it/s] 50%|█████ | 25/50 [00:06<00:06, 3.70it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.70it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.70it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.70it/s] 60%|██████ | 30/50 [00:08<00:05, 3.70it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.70it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.70it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.70it/s] 70%|███████ | 35/50 [00:09<00:04, 3.70it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.70it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.70it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.70it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.70it/s] 80%|████████ | 40/50 [00:10<00:02, 3.70it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.69it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.70it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.70it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.70it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.70it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.70it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.70it/s] 100%|██████████| 50/50 [00:13<00:00, 3.69it/s] 100%|██████████| 50/50 [00:13<00:00, 3.70it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beIDoswqettbcf6dxmh5ynmekxtrxeStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARA, velvet barbie flower slime
- refine
- no_refiner
- scheduler
- DDIM
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARA, velvet barbie flower slime", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARA, velvet barbie flower slime", refine: "no_refiner", scheduler: "DDIM", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARA, velvet barbie flower slime", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARA, velvet barbie flower slime", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T20:21:26.692943Z", "created_at": "2023-09-27T20:21:10.791407Z", "data_removed": false, "error": null, "id": "oswqettbcf6dxmh5ynmekxtrxe", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARA, velvet barbie flower slime", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 38791\nPrompt: In the style of GRINTHARA, velvet barbie flower slime\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.71it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.70it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.70it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.69it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.69it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.68it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.68it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.69it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.69it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.69it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.69it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.70it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.70it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.70it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.70it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.70it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.70it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.70it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.70it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.70it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.70it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.70it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.70it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.70it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.70it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.69it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.69it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.69it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.70it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.70it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.69it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.69it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.69it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.69it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.69it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.69it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.69it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.69it/s]", "metrics": { "predict_time": 15.903637, "total_time": 15.901536 }, "output": [ "https://pbxt.replicate.delivery/0bviowG8ELJ4NZfyaC3RwWxEfnXZSsfV8tAcd4Y6cKTLGIRjA/out-0.png" ], "started_at": "2023-09-27T20:21:10.789306Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/oswqettbcf6dxmh5ynmekxtrxe", "cancel": "https://api.replicate.com/v1/predictions/oswqettbcf6dxmh5ynmekxtrxe/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 38791 Prompt: In the style of GRINTHARA, velvet barbie flower slime txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.71it/s] 4%|▍ | 2/50 [00:00<00:12, 3.70it/s] 6%|▌ | 3/50 [00:00<00:12, 3.70it/s] 8%|▊ | 4/50 [00:01<00:12, 3.69it/s] 10%|█ | 5/50 [00:01<00:12, 3.69it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.68it/s] 20%|██ | 10/50 [00:02<00:10, 3.68it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.69it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.69it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.69it/s] 30%|███ | 15/50 [00:04<00:09, 3.69it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.70it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.70it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.70it/s] 40%|████ | 20/50 [00:05<00:08, 3.70it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.70it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.70it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.70it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.70it/s] 50%|█████ | 25/50 [00:06<00:06, 3.70it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.70it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.70it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.70it/s] 60%|██████ | 30/50 [00:08<00:05, 3.70it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.70it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.69it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.69it/s] 70%|███████ | 35/50 [00:09<00:04, 3.69it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.70it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.70it/s] 80%|████████ | 40/50 [00:10<00:02, 3.69it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.69it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.69it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.69it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.69it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.69it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.69it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.69it/s] 100%|██████████| 50/50 [00:13<00:00, 3.69it/s] 100%|██████████| 50/50 [00:13<00:00, 3.69it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beIDglgquptbnmu3j6fvgmz3jsgmjiStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARAPE, reverse split cotton hair teeth fish
- refine
- no_refiner
- scheduler
- DDIM
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", refine: "no_refiner", scheduler: "DDIM", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-28T18:22:06.150059Z", "created_at": "2023-09-28T18:21:50.319103Z", "data_removed": false, "error": null, "id": "glgquptbnmu3j6fvgmz3jsgmji", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 53242\nPrompt: In the style of GRINTHARAPE, reverse split cotton hair teeth fish\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.67it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.67it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.67it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.66it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.66it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.66it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.66it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.66it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.66it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.65it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.65it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.65it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.65it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.65it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.64it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.65it/s]\n 34%|███▍ | 17/50 [00:04<00:09, 3.64it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.65it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.65it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.64it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.64it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.64it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.64it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.64it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.64it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.64it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.64it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.64it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.64it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.64it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.64it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.63it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.64it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.64it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.64it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.64it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.64it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.64it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.63it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.63it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.64it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.64it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.63it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.64it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.64it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.63it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.63it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.63it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.63it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.63it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.64it/s]", "metrics": { "predict_time": 15.8397, "total_time": 15.830956 }, "output": [ "https://pbxt.replicate.delivery/gm2D7wcyD7Y9Al3HVlmrqw2D5LL0ZYiceKeYaHChUz9NZ3oRA/out-0.png" ], "started_at": "2023-09-28T18:21:50.310359Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/glgquptbnmu3j6fvgmz3jsgmji", "cancel": "https://api.replicate.com/v1/predictions/glgquptbnmu3j6fvgmz3jsgmji/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 53242 Prompt: In the style of GRINTHARAPE, reverse split cotton hair teeth fish txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.67it/s] 4%|▍ | 2/50 [00:00<00:13, 3.67it/s] 6%|▌ | 3/50 [00:00<00:12, 3.67it/s] 8%|▊ | 4/50 [00:01<00:12, 3.66it/s] 10%|█ | 5/50 [00:01<00:12, 3.66it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.66it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.66it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.66it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.66it/s] 20%|██ | 10/50 [00:02<00:10, 3.65it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.65it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.65it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.65it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.65it/s] 30%|███ | 15/50 [00:04<00:09, 3.64it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.65it/s] 34%|███▍ | 17/50 [00:04<00:09, 3.64it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.65it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.65it/s] 40%|████ | 20/50 [00:05<00:08, 3.64it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.64it/s] 44%|████▍ | 22/50 [00:06<00:07, 3.64it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.64it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.64it/s] 50%|█████ | 25/50 [00:06<00:06, 3.64it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.64it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.64it/s] 56%|█████▌ | 28/50 [00:07<00:06, 3.64it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.64it/s] 60%|██████ | 30/50 [00:08<00:05, 3.64it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.64it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.63it/s] 66%|██████▌ | 33/50 [00:09<00:04, 3.64it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.64it/s] 70%|███████ | 35/50 [00:09<00:04, 3.64it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.64it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.64it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.64it/s] 78%|███████▊ | 39/50 [00:10<00:03, 3.63it/s] 80%|████████ | 40/50 [00:10<00:02, 3.63it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.64it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.64it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.63it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.64it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.64it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.63it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.63it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.63it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.63it/s] 100%|██████████| 50/50 [00:13<00:00, 3.63it/s] 100%|██████████| 50/50 [00:13<00:00, 3.64it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beIDqterk2tbpcpz2if6tzdbgr4ikqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARAPE, reverse split cotton hair teeth fish
- refine
- no_refiner
- scheduler
- DDIM
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", refine: "no_refiner", scheduler: "DDIM", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-28T18:28:59.944258Z", "created_at": "2023-09-28T18:28:44.158236Z", "data_removed": false, "error": null, "id": "qterk2tbpcpz2if6tzdbgr4ikq", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth fish", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 37482\nPrompt: In the style of GRINTHARAPE, reverse split cotton hair teeth fish\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.68it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.67it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.66it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.66it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.65it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.64it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.65it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.64it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.64it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.64it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.64it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.64it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.64it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.63it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.63it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.64it/s]\n 34%|███▍ | 17/50 [00:04<00:09, 3.63it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.63it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.63it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.63it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.63it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.63it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.63it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.63it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.62it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.62it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.62it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.62it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.62it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.62it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.63it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.62it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.62it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.63it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.63it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.63it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.62it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.62it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.62it/s]\n 80%|████████ | 40/50 [00:11<00:02, 3.62it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.63it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.62it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.62it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.62it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.62it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.62it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.62it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.62it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.62it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.62it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.63it/s]", "metrics": { "predict_time": 15.814991, "total_time": 15.786022 }, "output": [ "https://pbxt.replicate.delivery/VnFTjhR05GJKM9iM8RNOaJBL9vQLsqSK9CAUCRc5eiH1vb0IA/out-0.png" ], "started_at": "2023-09-28T18:28:44.129267Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/qterk2tbpcpz2if6tzdbgr4ikq", "cancel": "https://api.replicate.com/v1/predictions/qterk2tbpcpz2if6tzdbgr4ikq/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 37482 Prompt: In the style of GRINTHARAPE, reverse split cotton hair teeth fish txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.68it/s] 4%|▍ | 2/50 [00:00<00:13, 3.67it/s] 6%|▌ | 3/50 [00:00<00:12, 3.66it/s] 8%|▊ | 4/50 [00:01<00:12, 3.66it/s] 10%|█ | 5/50 [00:01<00:12, 3.65it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.64it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.65it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.64it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.64it/s] 20%|██ | 10/50 [00:02<00:10, 3.64it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.64it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.64it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.64it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.63it/s] 30%|███ | 15/50 [00:04<00:09, 3.63it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.64it/s] 34%|███▍ | 17/50 [00:04<00:09, 3.63it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.63it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.63it/s] 40%|████ | 20/50 [00:05<00:08, 3.63it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.63it/s] 44%|████▍ | 22/50 [00:06<00:07, 3.63it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.63it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.63it/s] 50%|█████ | 25/50 [00:06<00:06, 3.62it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.62it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.62it/s] 56%|█████▌ | 28/50 [00:07<00:06, 3.62it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.62it/s] 60%|██████ | 30/50 [00:08<00:05, 3.62it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.63it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.62it/s] 66%|██████▌ | 33/50 [00:09<00:04, 3.62it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.63it/s] 70%|███████ | 35/50 [00:09<00:04, 3.63it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.63it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.62it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.62it/s] 78%|███████▊ | 39/50 [00:10<00:03, 3.62it/s] 80%|████████ | 40/50 [00:11<00:02, 3.62it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.63it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.62it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.62it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.62it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.62it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.62it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.62it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.62it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.62it/s] 100%|██████████| 50/50 [00:13<00:00, 3.62it/s] 100%|██████████| 50/50 [00:13<00:00, 3.63it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beID4pckvblbibof7gz4euwg32skwyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARAPE, reverse split cotton hair teeth eel bulb
- refine
- no_refiner
- scheduler
- DDIM
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth eel bulb", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARAPE, reverse split cotton hair teeth eel bulb", refine: "no_refiner", scheduler: "DDIM", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth eel bulb", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth eel bulb", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-28T19:10:07.219503Z", "created_at": "2023-09-28T19:09:51.517472Z", "data_removed": false, "error": null, "id": "4pckvblbibof7gz4euwg32skwy", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair teeth eel bulb", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 41800\nPrompt: In the style of GRINTHARAPE, reverse split cotton hair teeth eel bulb\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.71it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.71it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.71it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.69it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.69it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.69it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.64it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.64it/s]\n 34%|███▍ | 17/50 [00:04<00:09, 3.65it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.66it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.66it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.66it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.67it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.67it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.67it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.67it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.67it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.67it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.67it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.67it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.67it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.67it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.66it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.67it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.67it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.66it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.66it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.66it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.66it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.66it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.66it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.66it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.66it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.66it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.66it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.66it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.66it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.66it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.66it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.66it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.66it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.67it/s]", "metrics": { "predict_time": 15.740864, "total_time": 15.702031 }, "output": [ "https://pbxt.replicate.delivery/hZM5qda2dSbsKhWO0vLWq3HKfvBb2NdHgPujcpOxwEGHDc0IA/out-0.png" ], "started_at": "2023-09-28T19:09:51.478639Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4pckvblbibof7gz4euwg32skwy", "cancel": "https://api.replicate.com/v1/predictions/4pckvblbibof7gz4euwg32skwy/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 41800 Prompt: In the style of GRINTHARAPE, reverse split cotton hair teeth eel bulb txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.71it/s] 4%|▍ | 2/50 [00:00<00:12, 3.71it/s] 6%|▌ | 3/50 [00:00<00:12, 3.71it/s] 8%|▊ | 4/50 [00:01<00:12, 3.69it/s] 10%|█ | 5/50 [00:01<00:12, 3.69it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s] 20%|██ | 10/50 [00:02<00:10, 3.69it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s] 30%|███ | 15/50 [00:04<00:09, 3.64it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.64it/s] 34%|███▍ | 17/50 [00:04<00:09, 3.65it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.66it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.66it/s] 40%|████ | 20/50 [00:05<00:08, 3.66it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.67it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.67it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.67it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.67it/s] 50%|█████ | 25/50 [00:06<00:06, 3.67it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.67it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.67it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.67it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.67it/s] 60%|██████ | 30/50 [00:08<00:05, 3.67it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.66it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.67it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.67it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.66it/s] 70%|███████ | 35/50 [00:09<00:04, 3.66it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.66it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.66it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.66it/s] 78%|███████▊ | 39/50 [00:10<00:03, 3.66it/s] 80%|████████ | 40/50 [00:10<00:02, 3.66it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.66it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.66it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.66it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.66it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.66it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.66it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.66it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.66it/s] 100%|██████████| 50/50 [00:13<00:00, 3.66it/s] 100%|██████████| 50/50 [00:13<00:00, 3.67it/s]Prediction
galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05beID5xe657lbk4ljqqelnsaaq5t5myStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of GRINTHARAPE, reverse split cotton hair nose shrimp
- refine
- no_refiner
- scheduler
- DDIM
- lora_scale
- 0.88
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- prompt_strength
- 1
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair nose shrimp", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", { input: { width: 1024, height: 1024, prompt: "In the style of GRINTHARAPE, reverse split cotton hair nose shrimp", refine: "no_refiner", scheduler: "DDIM", lora_scale: 0.88, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.6, negative_prompt: "", prompt_strength: 1, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "galleri5/alien-green:3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", input={ "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair nose shrimp", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run galleri5/alien-green using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair nose shrimp", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-28T20:37:38.408224Z", "created_at": "2023-09-28T20:37:22.812736Z", "data_removed": false, "error": null, "id": "5xe657lbk4ljqqelnsaaq5t5my", "input": { "width": 1024, "height": 1024, "prompt": "In the style of GRINTHARAPE, reverse split cotton hair nose shrimp", "refine": "no_refiner", "scheduler": "DDIM", "lora_scale": 0.88, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.6, "negative_prompt": "", "prompt_strength": 1, "num_inference_steps": 50 }, "logs": "Using seed: 4899\nPrompt: In the style of GRINTHARAPE, reverse split cotton hair nose shrimp\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.72it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.72it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.72it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.72it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.72it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.72it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.71it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.71it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.71it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.71it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.71it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.70it/s]\n 26%|██▌ | 13/50 [00:03<00:09, 3.70it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.70it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.70it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.70it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.70it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.70it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.65it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.67it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.67it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.69it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.69it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.70it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.70it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.70it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.70it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.70it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.70it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.70it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.69it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.69it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.69it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.69it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.69it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.69it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.69it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.69it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.69it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.69it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.69it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.69it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.69it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.69it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.69it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.70it/s]", "metrics": { "predict_time": 15.614544, "total_time": 15.595488 }, "output": [ "https://pbxt.replicate.delivery/kqXp5aeY51SOf0cw222pQX13myuT2aRQhsYU7p3L7LfiwyRjA/out-0.png" ], "started_at": "2023-09-28T20:37:22.793680Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5xe657lbk4ljqqelnsaaq5t5my", "cancel": "https://api.replicate.com/v1/predictions/5xe657lbk4ljqqelnsaaq5t5my/cancel" }, "version": "3be20de19393753415d9191c508481561c3ce8bdc8b4742a3dd6f20be7ed05be" }Generated inUsing seed: 4899 Prompt: In the style of GRINTHARAPE, reverse split cotton hair nose shrimp txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.72it/s] 4%|▍ | 2/50 [00:00<00:12, 3.72it/s] 6%|▌ | 3/50 [00:00<00:12, 3.72it/s] 8%|▊ | 4/50 [00:01<00:12, 3.72it/s] 10%|█ | 5/50 [00:01<00:12, 3.72it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.72it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.71it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.71it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.71it/s] 20%|██ | 10/50 [00:02<00:10, 3.71it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.71it/s] 24%|██▍ | 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