fofr / sdxl-ghostbusters
- Public
- 766 runs
-
L40S
- SDXL fine-tune
Prediction
fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20aIDj7wshkdbnbb4z3qm55sa4ox5fyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a TOK ghost in a film still from Ghostbusters
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.9
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "a TOK ghost in a film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/sdxl-ghostbusters using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a", { input: { width: 1024, height: 1024, prompt: "a TOK ghost in a film still from Ghostbusters", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.9, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 30 } } ); // 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 fofr/sdxl-ghostbusters using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a", input={ "width": 1024, "height": 1024, "prompt": "a TOK ghost in a film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.9, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-ghostbusters 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": "fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a", "input": { "width": 1024, "height": 1024, "prompt": "a TOK ghost in a film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-10-29T22:34:02.064174Z", "created_at": "2023-10-29T22:33:52.916298Z", "data_removed": false, "error": null, "id": "j7wshkdbnbb4z3qm55sa4ox5fy", "input": { "width": 1024, "height": 1024, "prompt": "a TOK ghost in a film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 2886\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a <s0><s1> ghost in a film still from Ghostbusters\ntxt2img mode\n 0%| | 0/21 [00:00<?, ?it/s]\n 5%|▍ | 1/21 [00:00<00:05, 3.64it/s]\n 10%|▉ | 2/21 [00:00<00:05, 3.64it/s]\n 14%|█▍ | 3/21 [00:00<00:04, 3.64it/s]\n 19%|█▉ | 4/21 [00:01<00:04, 3.64it/s]\n 24%|██▍ | 5/21 [00:01<00:04, 3.64it/s]\n 29%|██▊ | 6/21 [00:01<00:04, 3.64it/s]\n 33%|███▎ | 7/21 [00:01<00:03, 3.64it/s]\n 38%|███▊ | 8/21 [00:02<00:03, 3.64it/s]\n 43%|████▎ | 9/21 [00:02<00:03, 3.64it/s]\n 48%|████▊ | 10/21 [00:02<00:03, 3.64it/s]\n 52%|█████▏ | 11/21 [00:03<00:02, 3.63it/s]\n 57%|█████▋ | 12/21 [00:03<00:02, 3.63it/s]\n 62%|██████▏ | 13/21 [00:03<00:02, 3.63it/s]\n 67%|██████▋ | 14/21 [00:03<00:01, 3.63it/s]\n 71%|███████▏ | 15/21 [00:04<00:01, 3.63it/s]\n 76%|███████▌ | 16/21 [00:04<00:01, 3.63it/s]\n 81%|████████ | 17/21 [00:04<00:01, 3.63it/s]\n 86%|████████▌ | 18/21 [00:04<00:00, 3.63it/s]\n 90%|█████████ | 19/21 [00:05<00:00, 3.62it/s]\n 95%|█████████▌| 20/21 [00:05<00:00, 3.62it/s]\n100%|██████████| 21/21 [00:05<00:00, 3.62it/s]\n100%|██████████| 21/21 [00:05<00:00, 3.63it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 4.23it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 4.21it/s]\n100%|██████████| 3/3 [00:00<00:00, 4.20it/s]\n100%|██████████| 3/3 [00:00<00:00, 4.21it/s]", "metrics": { "predict_time": 8.685183, "total_time": 9.147876 }, "output": [ "https://pbxt.replicate.delivery/EgN30uR0H85iL5pcw0OTih2J52TDO9xa7I0j4Fmudud2PycE/out-0.png" ], "started_at": "2023-10-29T22:33:53.378991Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/j7wshkdbnbb4z3qm55sa4ox5fy", "cancel": "https://api.replicate.com/v1/predictions/j7wshkdbnbb4z3qm55sa4ox5fy/cancel" }, "version": "17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a" }Generated inUsing seed: 2886 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a <s0><s1> ghost in a film still from Ghostbusters txt2img mode 0%| | 0/21 [00:00<?, ?it/s] 5%|▍ | 1/21 [00:00<00:05, 3.64it/s] 10%|▉ | 2/21 [00:00<00:05, 3.64it/s] 14%|█▍ | 3/21 [00:00<00:04, 3.64it/s] 19%|█▉ | 4/21 [00:01<00:04, 3.64it/s] 24%|██▍ | 5/21 [00:01<00:04, 3.64it/s] 29%|██▊ | 6/21 [00:01<00:04, 3.64it/s] 33%|███▎ | 7/21 [00:01<00:03, 3.64it/s] 38%|███▊ | 8/21 [00:02<00:03, 3.64it/s] 43%|████▎ | 9/21 [00:02<00:03, 3.64it/s] 48%|████▊ | 10/21 [00:02<00:03, 3.64it/s] 52%|█████▏ | 11/21 [00:03<00:02, 3.63it/s] 57%|█████▋ | 12/21 [00:03<00:02, 3.63it/s] 62%|██████▏ | 13/21 [00:03<00:02, 3.63it/s] 67%|██████▋ | 14/21 [00:03<00:01, 3.63it/s] 71%|███████▏ | 15/21 [00:04<00:01, 3.63it/s] 76%|███████▌ | 16/21 [00:04<00:01, 3.63it/s] 81%|████████ | 17/21 [00:04<00:01, 3.63it/s] 86%|████████▌ | 18/21 [00:04<00:00, 3.63it/s] 90%|█████████ | 19/21 [00:05<00:00, 3.62it/s] 95%|█████████▌| 20/21 [00:05<00:00, 3.62it/s] 100%|██████████| 21/21 [00:05<00:00, 3.62it/s] 100%|██████████| 21/21 [00:05<00:00, 3.63it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 4.23it/s] 67%|██████▋ | 2/3 [00:00<00:00, 4.21it/s] 100%|██████████| 3/3 [00:00<00:00, 4.20it/s] 100%|██████████| 3/3 [00:00<00:00, 4.21it/s]Prediction
fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20aIDuopxkglbbbh2bl5diygtssr5aiStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- a TOK ghost in a park, film still from Ghostbusters
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.9
- negative_prompt
- disfigured, ugly, broken, grinch
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1152, "height": 768, "prompt": "a TOK ghost in a park, film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "disfigured, ugly, broken, grinch", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/sdxl-ghostbusters using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a", { input: { width: 1152, height: 768, prompt: "a TOK ghost in a park, film still from Ghostbusters", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.9, negative_prompt: "disfigured, ugly, broken, grinch", prompt_strength: 0.8, num_inference_steps: 30 } } ); // 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 fofr/sdxl-ghostbusters using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a", input={ "width": 1152, "height": 768, "prompt": "a TOK ghost in a park, film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.9, "negative_prompt": "disfigured, ugly, broken, grinch", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-ghostbusters 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": "fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a", "input": { "width": 1152, "height": 768, "prompt": "a TOK ghost in a park, film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "disfigured, ugly, broken, grinch", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-10-29T22:36:53.629541Z", "created_at": "2023-10-29T22:36:44.437857Z", "data_removed": false, "error": null, "id": "uopxkglbbbh2bl5diygtssr5ai", "input": { "width": 1152, "height": 768, "prompt": "a TOK ghost in a park, film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "disfigured, ugly, broken, grinch", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 1051\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a <s0><s1> ghost in a park, film still from Ghostbusters\ntxt2img mode\n 0%| | 0/21 [00:00<?, ?it/s]\n 5%|▍ | 1/21 [00:00<00:04, 4.29it/s]\n 10%|▉ | 2/21 [00:00<00:04, 4.28it/s]\n 14%|█▍ | 3/21 [00:00<00:04, 4.29it/s]\n 19%|█▉ | 4/21 [00:00<00:03, 4.29it/s]\n 24%|██▍ | 5/21 [00:01<00:03, 4.29it/s]\n 29%|██▊ | 6/21 [00:01<00:03, 4.30it/s]\n 33%|███▎ | 7/21 [00:01<00:03, 4.29it/s]\n 38%|███▊ | 8/21 [00:01<00:03, 4.30it/s]\n 43%|████▎ | 9/21 [00:02<00:02, 4.30it/s]\n 48%|████▊ | 10/21 [00:02<00:02, 4.30it/s]\n 52%|█████▏ | 11/21 [00:02<00:02, 4.30it/s]\n 57%|█████▋ | 12/21 [00:02<00:02, 4.30it/s]\n 62%|██████▏ | 13/21 [00:03<00:01, 4.30it/s]\n 67%|██████▋ | 14/21 [00:03<00:01, 4.30it/s]\n 71%|███████▏ | 15/21 [00:03<00:01, 4.30it/s]\n 76%|███████▌ | 16/21 [00:03<00:01, 4.30it/s]\n 81%|████████ | 17/21 [00:03<00:00, 4.30it/s]\n 86%|████████▌ | 18/21 [00:04<00:00, 4.30it/s]\n 90%|█████████ | 19/21 [00:04<00:00, 4.29it/s]\n 95%|█████████▌| 20/21 [00:04<00:00, 4.29it/s]\n100%|██████████| 21/21 [00:04<00:00, 4.29it/s]\n100%|██████████| 21/21 [00:04<00:00, 4.29it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.47it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 5.46it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.47it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.46it/s]", "metrics": { "predict_time": 7.358555, "total_time": 9.191684 }, "output": [ "https://pbxt.replicate.delivery/HOt3QRVA3rKoG15I2KZw4YqL05ldo4vjyhjpCtACyCQhQycE/out-0.png" ], "started_at": "2023-10-29T22:36:46.270986Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/uopxkglbbbh2bl5diygtssr5ai", "cancel": "https://api.replicate.com/v1/predictions/uopxkglbbbh2bl5diygtssr5ai/cancel" }, "version": "17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a" }Generated inUsing seed: 1051 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a <s0><s1> ghost in a park, film still from Ghostbusters txt2img mode 0%| | 0/21 [00:00<?, ?it/s] 5%|▍ | 1/21 [00:00<00:04, 4.29it/s] 10%|▉ | 2/21 [00:00<00:04, 4.28it/s] 14%|█▍ | 3/21 [00:00<00:04, 4.29it/s] 19%|█▉ | 4/21 [00:00<00:03, 4.29it/s] 24%|██▍ | 5/21 [00:01<00:03, 4.29it/s] 29%|██▊ | 6/21 [00:01<00:03, 4.30it/s] 33%|███▎ | 7/21 [00:01<00:03, 4.29it/s] 38%|███▊ | 8/21 [00:01<00:03, 4.30it/s] 43%|████▎ | 9/21 [00:02<00:02, 4.30it/s] 48%|████▊ | 10/21 [00:02<00:02, 4.30it/s] 52%|█████▏ | 11/21 [00:02<00:02, 4.30it/s] 57%|█████▋ | 12/21 [00:02<00:02, 4.30it/s] 62%|██████▏ | 13/21 [00:03<00:01, 4.30it/s] 67%|██████▋ | 14/21 [00:03<00:01, 4.30it/s] 71%|███████▏ | 15/21 [00:03<00:01, 4.30it/s] 76%|███████▌ | 16/21 [00:03<00:01, 4.30it/s] 81%|████████ | 17/21 [00:03<00:00, 4.30it/s] 86%|████████▌ | 18/21 [00:04<00:00, 4.30it/s] 90%|█████████ | 19/21 [00:04<00:00, 4.29it/s] 95%|█████████▌| 20/21 [00:04<00:00, 4.29it/s] 100%|██████████| 21/21 [00:04<00:00, 4.29it/s] 100%|██████████| 21/21 [00:04<00:00, 4.29it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.47it/s] 67%|██████▋ | 2/3 [00:00<00:00, 5.46it/s] 100%|██████████| 3/3 [00:00<00:00, 5.47it/s] 100%|██████████| 3/3 [00:00<00:00, 5.46it/s]Prediction
fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20aIDgakdh5lbbhbntn44zl45hb5xmmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- a giant TOK monster ghost in on a street, a film still from Ghostbusters
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.9
- negative_prompt
- disfigured, ugly, broken, grinch
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1152, "height": 768, "prompt": "a giant TOK monster ghost in on a street, a film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "disfigured, ugly, broken, grinch", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/sdxl-ghostbusters using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a", { input: { width: 1152, height: 768, prompt: "a giant TOK monster ghost in on a street, a film still from Ghostbusters", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.9, negative_prompt: "disfigured, ugly, broken, grinch", prompt_strength: 0.8, num_inference_steps: 30 } } ); // 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 fofr/sdxl-ghostbusters using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a", input={ "width": 1152, "height": 768, "prompt": "a giant TOK monster ghost in on a street, a film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.9, "negative_prompt": "disfigured, ugly, broken, grinch", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-ghostbusters 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": "fofr/sdxl-ghostbusters:17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a", "input": { "width": 1152, "height": 768, "prompt": "a giant TOK monster ghost in on a street, a film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "disfigured, ugly, broken, grinch", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-10-29T22:40:11.993966Z", "created_at": "2023-10-29T22:40:03.731554Z", "data_removed": false, "error": null, "id": "gakdh5lbbhbntn44zl45hb5xmm", "input": { "width": 1152, "height": 768, "prompt": "a giant TOK monster ghost in on a street, a film still from Ghostbusters", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "disfigured, ugly, broken, grinch", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 24480\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a giant <s0><s1> monster ghost in on a street, a film still from Ghostbusters\ntxt2img mode\n 0%| | 0/21 [00:00<?, ?it/s]\n 5%|▍ | 1/21 [00:00<00:04, 4.33it/s]\n 10%|▉ | 2/21 [00:00<00:04, 4.31it/s]\n 14%|█▍ | 3/21 [00:00<00:04, 4.31it/s]\n 19%|█▉ | 4/21 [00:00<00:03, 4.31it/s]\n 24%|██▍ | 5/21 [00:01<00:03, 4.31it/s]\n 29%|██▊ | 6/21 [00:01<00:03, 4.32it/s]\n 33%|███▎ | 7/21 [00:01<00:03, 4.31it/s]\n 38%|███▊ | 8/21 [00:01<00:03, 4.31it/s]\n 43%|████▎ | 9/21 [00:02<00:02, 4.31it/s]\n 48%|████▊ | 10/21 [00:02<00:02, 4.31it/s]\n 52%|█████▏ | 11/21 [00:02<00:02, 4.31it/s]\n 57%|█████▋ | 12/21 [00:02<00:02, 4.31it/s]\n 62%|██████▏ | 13/21 [00:03<00:01, 4.30it/s]\n 67%|██████▋ | 14/21 [00:03<00:01, 4.30it/s]\n 71%|███████▏ | 15/21 [00:03<00:01, 4.30it/s]\n 76%|███████▌ | 16/21 [00:03<00:01, 4.30it/s]\n 81%|████████ | 17/21 [00:03<00:00, 4.29it/s]\n 86%|████████▌ | 18/21 [00:04<00:00, 4.29it/s]\n 90%|█████████ | 19/21 [00:04<00:00, 4.29it/s]\n 95%|█████████▌| 20/21 [00:04<00:00, 4.29it/s]\n100%|██████████| 21/21 [00:04<00:00, 4.29it/s]\n100%|██████████| 21/21 [00:04<00:00, 4.30it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.51it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 5.49it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.48it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.48it/s]", "metrics": { "predict_time": 7.35539, "total_time": 8.262412 }, "output": [ "https://pbxt.replicate.delivery/QUXoD7xDKSI2O1LS2wZXesIj2GDvVJVwvFpIqseoySeWKSmjA/out-0.png" ], "started_at": "2023-10-29T22:40:04.638576Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gakdh5lbbhbntn44zl45hb5xmm", "cancel": "https://api.replicate.com/v1/predictions/gakdh5lbbhbntn44zl45hb5xmm/cancel" }, "version": "17658fb151a7dd2fe9a0043990c24913d7b97a6b35dcd953a27a366fedc4e20a" }Generated inUsing seed: 24480 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a giant <s0><s1> monster ghost in on a street, a film still from Ghostbusters txt2img mode 0%| | 0/21 [00:00<?, ?it/s] 5%|▍ | 1/21 [00:00<00:04, 4.33it/s] 10%|▉ | 2/21 [00:00<00:04, 4.31it/s] 14%|█▍ | 3/21 [00:00<00:04, 4.31it/s] 19%|█▉ | 4/21 [00:00<00:03, 4.31it/s] 24%|██▍ | 5/21 [00:01<00:03, 4.31it/s] 29%|██▊ | 6/21 [00:01<00:03, 4.32it/s] 33%|███▎ | 7/21 [00:01<00:03, 4.31it/s] 38%|███▊ | 8/21 [00:01<00:03, 4.31it/s] 43%|████▎ | 9/21 [00:02<00:02, 4.31it/s] 48%|████▊ | 10/21 [00:02<00:02, 4.31it/s] 52%|█████▏ | 11/21 [00:02<00:02, 4.31it/s] 57%|█████▋ | 12/21 [00:02<00:02, 4.31it/s] 62%|██████▏ | 13/21 [00:03<00:01, 4.30it/s] 67%|██████▋ | 14/21 [00:03<00:01, 4.30it/s] 71%|███████▏ | 15/21 [00:03<00:01, 4.30it/s] 76%|███████▌ | 16/21 [00:03<00:01, 4.30it/s] 81%|████████ | 17/21 [00:03<00:00, 4.29it/s] 86%|████████▌ | 18/21 [00:04<00:00, 4.29it/s] 90%|█████████ | 19/21 [00:04<00:00, 4.29it/s] 95%|█████████▌| 20/21 [00:04<00:00, 4.29it/s] 100%|██████████| 21/21 [00:04<00:00, 4.29it/s] 100%|██████████| 21/21 [00:04<00:00, 4.30it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.51it/s] 67%|██████▋ | 2/3 [00:00<00:00, 5.49it/s] 100%|██████████| 3/3 [00:00<00:00, 5.48it/s] 100%|██████████| 3/3 [00:00<00:00, 5.48it/s]
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