felixyifeiwang / eom-phase1
(Updated 7 months, 3 weeks ago)
- Public
- 2.1K runs
Prediction
felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1ID3ys01zyg61rgm0cgv2d9t8e5pmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a full-body TOK chibi character, death god, empty background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- out of frame, mutated, deformed, extras, sprites
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, death god, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 }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 felixyifeiwang/eom-phase1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", { input: { width: 1024, height: 1024, prompt: "a full-body TOK chibi character, death god, empty background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "out of frame, mutated, deformed, extras, sprites", prompt_strength: 0.8, 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 felixyifeiwang/eom-phase1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", input={ "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, death god, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run felixyifeiwang/eom-phase1 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": "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", "input": { "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, death god, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "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": "2024-07-22T04:02:41.547655Z", "created_at": "2024-07-22T04:02:22.896000Z", "data_removed": false, "error": null, "id": "3ys01zyg61rgm0cgv2d9t8e5pm", "input": { "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, death god, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 22583\nEnsuring enough disk space...\nFree disk space: 1867501723648\nDownloading weights: https://replicate.delivery/pbxt/07TYqcL4ETIEPlgPW7EWhr93kl7WffLoas7fYMr2CemIvarMB/trained_model.tar\n2024-07-22T04:02:24Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/004e3e38603a1b4c url=https://replicate.delivery/pbxt/07TYqcL4ETIEPlgPW7EWhr93kl7WffLoas7fYMr2CemIvarMB/trained_model.tar\n2024-07-22T04:02:26Z | INFO | [ Complete ] dest=/src/weights-cache/004e3e38603a1b4c size=\"186 MB\" total_elapsed=1.838s url=https://replicate.delivery/pbxt/07TYqcL4ETIEPlgPW7EWhr93kl7WffLoas7fYMr2CemIvarMB/trained_model.tar\nb''\nDownloaded weights in 1.9289028644561768 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a full-body <s0><s1> chibi character, death god, empty background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]/usr/local/lib/python3.9/site-packages/diffusers/models/attention_processor.py:1946: FutureWarning: `LoRAAttnProcessor2_0` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor2_0 instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights`\ndeprecate(\n 2%|▏ | 1/50 [00:00<00:11, 4.28it/s]\n 4%|▍ | 2/50 [00:00<00:11, 4.26it/s]\n 6%|▌ | 3/50 [00:00<00:11, 4.26it/s]\n 8%|▊ | 4/50 [00:00<00:10, 4.24it/s]\n 10%|█ | 5/50 [00:01<00:10, 4.24it/s]\n 12%|█▏ | 6/50 [00:01<00:10, 4.24it/s]\n 14%|█▍ | 7/50 [00:01<00:10, 4.24it/s]\n 16%|█▌ | 8/50 [00:01<00:09, 4.23it/s]\n 18%|█▊ | 9/50 [00:02<00:09, 4.23it/s]\n 20%|██ | 10/50 [00:02<00:09, 4.23it/s]\n 22%|██▏ | 11/50 [00:02<00:09, 4.24it/s]\n 24%|██▍ | 12/50 [00:02<00:08, 4.25it/s]\n 26%|██▌ | 13/50 [00:03<00:08, 4.25it/s]\n 28%|██▊ | 14/50 [00:03<00:08, 4.26it/s]\n 30%|███ | 15/50 [00:03<00:08, 4.26it/s]\n 32%|███▏ | 16/50 [00:03<00:07, 4.26it/s]\n 34%|███▍ | 17/50 [00:04<00:07, 4.26it/s]\n 36%|███▌ | 18/50 [00:04<00:07, 4.26it/s]\n 38%|███▊ | 19/50 [00:04<00:07, 4.26it/s]\n 40%|████ | 20/50 [00:04<00:07, 4.25it/s]\n 42%|████▏ | 21/50 [00:04<00:06, 4.25it/s]\n 44%|████▍ | 22/50 [00:05<00:06, 4.25it/s]\n 46%|████▌ | 23/50 [00:05<00:06, 4.25it/s]\n 48%|████▊ | 24/50 [00:05<00:06, 4.26it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.25it/s]\n 52%|█████▏ | 26/50 [00:06<00:05, 4.25it/s]\n 54%|█████▍ | 27/50 [00:06<00:05, 4.26it/s]\n 56%|█████▌ | 28/50 [00:06<00:05, 4.26it/s]\n 58%|█████▊ | 29/50 [00:06<00:04, 4.26it/s]\n 60%|██████ | 30/50 [00:07<00:04, 4.26it/s]\n 62%|██████▏ | 31/50 [00:07<00:04, 4.25it/s]\n 64%|██████▍ | 32/50 [00:07<00:04, 4.25it/s]\n 66%|██████▌ | 33/50 [00:07<00:03, 4.25it/s]\n 68%|██████▊ | 34/50 [00:07<00:03, 4.25it/s]\n 70%|███████ | 35/50 [00:08<00:03, 4.23it/s]\n 72%|███████▏ | 36/50 [00:08<00:03, 4.21it/s]\n 74%|███████▍ | 37/50 [00:08<00:03, 4.23it/s]\n 76%|███████▌ | 38/50 [00:08<00:02, 4.23it/s]\n 78%|███████▊ | 39/50 [00:09<00:02, 4.24it/s]\n 80%|████████ | 40/50 [00:09<00:02, 4.24it/s]\n 82%|████████▏ | 41/50 [00:09<00:02, 4.24it/s]\n 84%|████████▍ | 42/50 [00:09<00:01, 4.24it/s]\n 86%|████████▌ | 43/50 [00:10<00:01, 4.25it/s]\n 88%|████████▊ | 44/50 [00:10<00:01, 4.25it/s]\n 90%|█████████ | 45/50 [00:10<00:01, 4.24it/s]\n 92%|█████████▏| 46/50 [00:10<00:00, 4.25it/s]\n 94%|█████████▍| 47/50 [00:11<00:00, 4.25it/s]\n 96%|█████████▌| 48/50 [00:11<00:00, 4.25it/s]\n 98%|█████████▊| 49/50 [00:11<00:00, 4.24it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.25it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.25it/s]", "metrics": { "predict_time": 16.699743189, "total_time": 18.651655 }, "output": [ "https://replicate.delivery/pbxt/bFfyz7iwmhw6PiPRmkO3ZLVAdXG7ensfolju8RAaAsgDfirMB/out-0.png" ], "started_at": "2024-07-22T04:02:24.847912Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3ys01zyg61rgm0cgv2d9t8e5pm", "cancel": "https://api.replicate.com/v1/predictions/3ys01zyg61rgm0cgv2d9t8e5pm/cancel" }, "version": "d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1" }Generated inUsing seed: 22583 Ensuring enough disk space... Free disk space: 1867501723648 Downloading weights: https://replicate.delivery/pbxt/07TYqcL4ETIEPlgPW7EWhr93kl7WffLoas7fYMr2CemIvarMB/trained_model.tar 2024-07-22T04:02:24Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/004e3e38603a1b4c url=https://replicate.delivery/pbxt/07TYqcL4ETIEPlgPW7EWhr93kl7WffLoas7fYMr2CemIvarMB/trained_model.tar 2024-07-22T04:02:26Z | INFO | [ Complete ] dest=/src/weights-cache/004e3e38603a1b4c size="186 MB" total_elapsed=1.838s url=https://replicate.delivery/pbxt/07TYqcL4ETIEPlgPW7EWhr93kl7WffLoas7fYMr2CemIvarMB/trained_model.tar b'' Downloaded weights in 1.9289028644561768 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a full-body <s0><s1> chibi character, death god, empty background txt2img mode 0%| | 0/50 [00:00<?, ?it/s]/usr/local/lib/python3.9/site-packages/diffusers/models/attention_processor.py:1946: FutureWarning: `LoRAAttnProcessor2_0` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor2_0 instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights` deprecate( 2%|▏ | 1/50 [00:00<00:11, 4.28it/s] 4%|▍ | 2/50 [00:00<00:11, 4.26it/s] 6%|▌ | 3/50 [00:00<00:11, 4.26it/s] 8%|▊ | 4/50 [00:00<00:10, 4.24it/s] 10%|█ | 5/50 [00:01<00:10, 4.24it/s] 12%|█▏ | 6/50 [00:01<00:10, 4.24it/s] 14%|█▍ | 7/50 [00:01<00:10, 4.24it/s] 16%|█▌ | 8/50 [00:01<00:09, 4.23it/s] 18%|█▊ | 9/50 [00:02<00:09, 4.23it/s] 20%|██ | 10/50 [00:02<00:09, 4.23it/s] 22%|██▏ | 11/50 [00:02<00:09, 4.24it/s] 24%|██▍ | 12/50 [00:02<00:08, 4.25it/s] 26%|██▌ | 13/50 [00:03<00:08, 4.25it/s] 28%|██▊ | 14/50 [00:03<00:08, 4.26it/s] 30%|███ | 15/50 [00:03<00:08, 4.26it/s] 32%|███▏ | 16/50 [00:03<00:07, 4.26it/s] 34%|███▍ | 17/50 [00:04<00:07, 4.26it/s] 36%|███▌ | 18/50 [00:04<00:07, 4.26it/s] 38%|███▊ | 19/50 [00:04<00:07, 4.26it/s] 40%|████ | 20/50 [00:04<00:07, 4.25it/s] 42%|████▏ | 21/50 [00:04<00:06, 4.25it/s] 44%|████▍ | 22/50 [00:05<00:06, 4.25it/s] 46%|████▌ | 23/50 [00:05<00:06, 4.25it/s] 48%|████▊ | 24/50 [00:05<00:06, 4.26it/s] 50%|█████ | 25/50 [00:05<00:05, 4.25it/s] 52%|█████▏ | 26/50 [00:06<00:05, 4.25it/s] 54%|█████▍ | 27/50 [00:06<00:05, 4.26it/s] 56%|█████▌ | 28/50 [00:06<00:05, 4.26it/s] 58%|█████▊ | 29/50 [00:06<00:04, 4.26it/s] 60%|██████ | 30/50 [00:07<00:04, 4.26it/s] 62%|██████▏ | 31/50 [00:07<00:04, 4.25it/s] 64%|██████▍ | 32/50 [00:07<00:04, 4.25it/s] 66%|██████▌ | 33/50 [00:07<00:03, 4.25it/s] 68%|██████▊ | 34/50 [00:07<00:03, 4.25it/s] 70%|███████ | 35/50 [00:08<00:03, 4.23it/s] 72%|███████▏ | 36/50 [00:08<00:03, 4.21it/s] 74%|███████▍ | 37/50 [00:08<00:03, 4.23it/s] 76%|███████▌ | 38/50 [00:08<00:02, 4.23it/s] 78%|███████▊ | 39/50 [00:09<00:02, 4.24it/s] 80%|████████ | 40/50 [00:09<00:02, 4.24it/s] 82%|████████▏ | 41/50 [00:09<00:02, 4.24it/s] 84%|████████▍ | 42/50 [00:09<00:01, 4.24it/s] 86%|████████▌ | 43/50 [00:10<00:01, 4.25it/s] 88%|████████▊ | 44/50 [00:10<00:01, 4.25it/s] 90%|█████████ | 45/50 [00:10<00:01, 4.24it/s] 92%|█████████▏| 46/50 [00:10<00:00, 4.25it/s] 94%|█████████▍| 47/50 [00:11<00:00, 4.25it/s] 96%|█████████▌| 48/50 [00:11<00:00, 4.25it/s] 98%|█████████▊| 49/50 [00:11<00:00, 4.24it/s] 100%|██████████| 50/50 [00:11<00:00, 4.25it/s] 100%|██████████| 50/50 [00:11<00:00, 4.25it/s]Prediction
felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1ID6kxy4nkhb1rgm0cgv2e9mnagncStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a full-body TOK chibi character, a bearborn mage holding a arcana book, empty background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- out of frame, mutated, deformed, extras, sprites
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, a bearborn mage holding a arcana book, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 }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 felixyifeiwang/eom-phase1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", { input: { width: 1024, height: 1024, prompt: "a full-body TOK chibi character, a bearborn mage holding a arcana book, empty background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "out of frame, mutated, deformed, extras, sprites", prompt_strength: 0.8, 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 felixyifeiwang/eom-phase1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", input={ "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, a bearborn mage holding a arcana book, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run felixyifeiwang/eom-phase1 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": "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", "input": { "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, a bearborn mage holding a arcana book, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "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": "2024-07-22T04:04:26.749717Z", "created_at": "2024-07-22T04:04:09.688000Z", "data_removed": false, "error": null, "id": "6kxy4nkhb1rgm0cgv2e9mnagnc", "input": { "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, a bearborn mage holding a arcana book, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 66\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a full-body <s0><s1> chibi character, a bearborn mage holding a arcana book, empty background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:11, 4.28it/s]\n 4%|▍ | 2/50 [00:00<00:11, 4.26it/s]\n 6%|▌ | 3/50 [00:00<00:11, 4.25it/s]\n 8%|▊ | 4/50 [00:00<00:10, 4.25it/s]\n 10%|█ | 5/50 [00:01<00:10, 4.24it/s]\n 12%|█▏ | 6/50 [00:01<00:10, 4.24it/s]\n 14%|█▍ | 7/50 [00:01<00:10, 4.24it/s]\n 16%|█▌ | 8/50 [00:01<00:09, 4.25it/s]\n 18%|█▊ | 9/50 [00:02<00:09, 4.26it/s]\n 20%|██ | 10/50 [00:02<00:09, 4.26it/s]\n 22%|██▏ | 11/50 [00:02<00:09, 4.26it/s]\n 24%|██▍ | 12/50 [00:02<00:08, 4.24it/s]\n 26%|██▌ | 13/50 [00:03<00:08, 4.23it/s]\n 28%|██▊ | 14/50 [00:03<00:08, 4.23it/s]\n 30%|███ | 15/50 [00:03<00:08, 4.24it/s]\n 32%|███▏ | 16/50 [00:03<00:08, 4.25it/s]\n 34%|███▍ | 17/50 [00:04<00:07, 4.25it/s]\n 36%|███▌ | 18/50 [00:04<00:07, 4.26it/s]\n 38%|███▊ | 19/50 [00:04<00:07, 4.26it/s]\n 40%|████ | 20/50 [00:04<00:07, 4.25it/s]\n 42%|████▏ | 21/50 [00:04<00:06, 4.26it/s]\n 44%|████▍ | 22/50 [00:05<00:06, 4.26it/s]\n 46%|████▌ | 23/50 [00:05<00:06, 4.25it/s]\n 48%|████▊ | 24/50 [00:05<00:06, 4.25it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.26it/s]\n 52%|█████▏ | 26/50 [00:06<00:05, 4.26it/s]\n 54%|█████▍ | 27/50 [00:06<00:05, 4.26it/s]\n 56%|█████▌ | 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[00:11<00:00, 4.24it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.24it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.25it/s]", "metrics": { "predict_time": 14.568367427, "total_time": 17.061717 }, "output": [ "https://replicate.delivery/pbxt/6wkce8afmzoJ8kQmffGF9qxPa0RFpziUgfb3NuHY6hxXJGXZC/out-0.png" ], "started_at": "2024-07-22T04:04:12.181350Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/6kxy4nkhb1rgm0cgv2e9mnagnc", "cancel": "https://api.replicate.com/v1/predictions/6kxy4nkhb1rgm0cgv2e9mnagnc/cancel" }, "version": "d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1" }Generated inUsing seed: 66 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a full-body <s0><s1> chibi character, a bearborn mage holding a arcana book, empty background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:11, 4.28it/s] 4%|▍ | 2/50 [00:00<00:11, 4.26it/s] 6%|▌ | 3/50 [00:00<00:11, 4.25it/s] 8%|▊ | 4/50 [00:00<00:10, 4.25it/s] 10%|█ | 5/50 [00:01<00:10, 4.24it/s] 12%|█▏ | 6/50 [00:01<00:10, 4.24it/s] 14%|█▍ | 7/50 [00:01<00:10, 4.24it/s] 16%|█▌ | 8/50 [00:01<00:09, 4.25it/s] 18%|█▊ | 9/50 [00:02<00:09, 4.26it/s] 20%|██ | 10/50 [00:02<00:09, 4.26it/s] 22%|██▏ | 11/50 [00:02<00:09, 4.26it/s] 24%|██▍ | 12/50 [00:02<00:08, 4.24it/s] 26%|██▌ | 13/50 [00:03<00:08, 4.23it/s] 28%|██▊ | 14/50 [00:03<00:08, 4.23it/s] 30%|███ | 15/50 [00:03<00:08, 4.24it/s] 32%|███▏ | 16/50 [00:03<00:08, 4.25it/s] 34%|███▍ | 17/50 [00:04<00:07, 4.25it/s] 36%|███▌ | 18/50 [00:04<00:07, 4.26it/s] 38%|███▊ | 19/50 [00:04<00:07, 4.26it/s] 40%|████ | 20/50 [00:04<00:07, 4.25it/s] 42%|████▏ | 21/50 [00:04<00:06, 4.26it/s] 44%|████▍ | 22/50 [00:05<00:06, 4.26it/s] 46%|████▌ | 23/50 [00:05<00:06, 4.25it/s] 48%|████▊ | 24/50 [00:05<00:06, 4.25it/s] 50%|█████ | 25/50 [00:05<00:05, 4.26it/s] 52%|█████▏ | 26/50 [00:06<00:05, 4.26it/s] 54%|█████▍ | 27/50 [00:06<00:05, 4.26it/s] 56%|█████▌ | 28/50 [00:06<00:05, 4.26it/s] 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100%|██████████| 50/50 [00:11<00:00, 4.25it/s]Prediction
felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1IDwejte2fjf9rgg0cgv2fre695c0StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a full-body TOK chibi character, a rabitborn paladin holding a giant glowing shield, empty background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- out of frame, mutated, deformed, extras, sprites
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, a rabitborn paladin holding a giant glowing shield, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 }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 felixyifeiwang/eom-phase1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", { input: { width: 1024, height: 1024, prompt: "a full-body TOK chibi character, a rabitborn paladin holding a giant glowing shield, empty background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "out of frame, mutated, deformed, extras, sprites", prompt_strength: 0.8, 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 felixyifeiwang/eom-phase1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", input={ "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, a rabitborn paladin holding a giant glowing shield, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run felixyifeiwang/eom-phase1 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": "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", "input": { "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, a rabitborn paladin holding a giant glowing shield, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "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": "2024-07-22T04:08:18.709595Z", "created_at": "2024-07-22T04:07:59.354000Z", "data_removed": false, "error": null, "id": "wejte2fjf9rgg0cgv2fre695c0", "input": { "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, a rabitborn paladin holding a giant glowing shield, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 40186\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a full-body <s0><s1> chibi character, a rabitborn paladin holding a giant glowing shield, empty background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:11, 4.30it/s]\n 4%|▍ | 2/50 [00:00<00:11, 4.27it/s]\n 6%|▌ | 3/50 [00:00<00:11, 4.26it/s]\n 8%|▊ | 4/50 [00:00<00:10, 4.26it/s]\n 10%|█ | 5/50 [00:01<00:10, 4.25it/s]\n 12%|█▏ | 6/50 [00:01<00:10, 4.25it/s]\n 14%|█▍ | 7/50 [00:01<00:10, 4.25it/s]\n 16%|█▌ | 8/50 [00:01<00:09, 4.24it/s]\n 18%|█▊ | 9/50 [00:02<00:09, 4.24it/s]\n 20%|██ | 10/50 [00:02<00:09, 4.24it/s]\n 22%|██▏ | 11/50 [00:02<00:09, 4.23it/s]\n 24%|██▍ | 12/50 [00:02<00:08, 4.23it/s]\n 26%|██▌ | 13/50 [00:03<00:08, 4.24it/s]\n 28%|██▊ | 14/50 [00:03<00:08, 4.24it/s]\n 30%|███ | 15/50 [00:03<00:08, 4.23it/s]\n 32%|███▏ | 16/50 [00:03<00:08, 4.23it/s]\n 34%|███▍ | 17/50 [00:04<00:07, 4.23it/s]\n 36%|███▌ | 18/50 [00:04<00:07, 4.23it/s]\n 38%|███▊ | 19/50 [00:04<00:07, 4.23it/s]\n 40%|████ | 20/50 [00:04<00:07, 4.23it/s]\n 42%|████▏ | 21/50 [00:04<00:06, 4.23it/s]\n 44%|████▍ | 22/50 [00:05<00:06, 4.23it/s]\n 46%|████▌ | 23/50 [00:05<00:06, 4.23it/s]\n 48%|████▊ | 24/50 [00:05<00:06, 4.23it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.23it/s]\n 52%|█████▏ | 26/50 [00:06<00:05, 4.23it/s]\n 54%|█████▍ | 27/50 [00:06<00:05, 4.23it/s]\n 56%|█████▌ | 28/50 [00:06<00:05, 4.23it/s]\n 58%|█████▊ | 29/50 [00:06<00:04, 4.23it/s]\n 60%|██████ | 30/50 [00:07<00:04, 4.23it/s]\n 62%|██████▏ | 31/50 [00:07<00:04, 4.23it/s]\n 64%|██████▍ | 32/50 [00:07<00:04, 4.23it/s]\n 66%|██████▌ | 33/50 [00:07<00:04, 4.23it/s]\n 68%|██████▊ | 34/50 [00:08<00:03, 4.23it/s]\n 70%|███████ | 35/50 [00:08<00:03, 4.23it/s]\n 72%|███████▏ | 36/50 [00:08<00:03, 4.24it/s]\n 74%|███████▍ | 37/50 [00:08<00:03, 4.23it/s]\n 76%|███████▌ | 38/50 [00:08<00:02, 4.23it/s]\n 78%|███████▊ | 39/50 [00:09<00:02, 4.23it/s]\n 80%|████████ | 40/50 [00:09<00:02, 4.23it/s]\n 82%|████████▏ | 41/50 [00:09<00:02, 4.23it/s]\n 84%|████████▍ | 42/50 [00:09<00:01, 4.23it/s]\n 86%|████████▌ | 43/50 [00:10<00:01, 4.23it/s]\n 88%|████████▊ | 44/50 [00:10<00:01, 4.23it/s]\n 90%|█████████ | 45/50 [00:10<00:01, 4.23it/s]\n 92%|█████████▏| 46/50 [00:10<00:00, 4.23it/s]\n 94%|█████████▍| 47/50 [00:11<00:00, 4.23it/s]\n 96%|█████████▌| 48/50 [00:11<00:00, 4.24it/s]\n 98%|█████████▊| 49/50 [00:11<00:00, 4.23it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.23it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.23it/s]", "metrics": { "predict_time": 15.177828504, "total_time": 19.355595 }, "output": [ "https://replicate.delivery/pbxt/ejOW0SgL9nVwASv9ZubHg0dH5rcNXyc4ssdXIJ7p22GZaclJA/out-0.png" ], "started_at": "2024-07-22T04:08:03.531767Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/wejte2fjf9rgg0cgv2fre695c0", "cancel": "https://api.replicate.com/v1/predictions/wejte2fjf9rgg0cgv2fre695c0/cancel" }, "version": "d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1" }Generated inUsing seed: 40186 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a full-body <s0><s1> chibi character, a rabitborn paladin holding a giant glowing shield, empty background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:11, 4.30it/s] 4%|▍ | 2/50 [00:00<00:11, 4.27it/s] 6%|▌ | 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100%|██████████| 50/50 [00:11<00:00, 4.23it/s] 100%|██████████| 50/50 [00:11<00:00, 4.23it/s]Prediction
felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1ID28fnj25p2xrgm0cgv2kvedf0z8StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a full-body TOK chibi character, cyberpunk neon girl holding a Gatling, empty background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- out of frame, mutated, deformed, extras, sprites
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, cyberpunk neon girl holding a Gatling, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 }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 felixyifeiwang/eom-phase1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", { input: { width: 1024, height: 1024, prompt: "a full-body TOK chibi character, cyberpunk neon girl holding a Gatling, empty background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "out of frame, mutated, deformed, extras, sprites", prompt_strength: 0.8, 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 felixyifeiwang/eom-phase1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", input={ "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, cyberpunk neon girl holding a Gatling, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run felixyifeiwang/eom-phase1 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": "felixyifeiwang/eom-phase1:d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1", "input": { "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, cyberpunk neon girl holding a Gatling, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "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": "2024-07-22T04:16:45.532542Z", "created_at": "2024-07-22T04:16:28.183000Z", "data_removed": false, "error": null, "id": "28fnj25p2xrgm0cgv2kvedf0z8", "input": { "width": 1024, "height": 1024, "prompt": "a full-body TOK chibi character, cyberpunk neon girl holding a Gatling, empty background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "out of frame, mutated, deformed, extras, sprites", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 30207\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a full-body <s0><s1> chibi character, cyberpunk neon girl holding a Gatling, empty background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:11, 4.30it/s]\n 4%|▍ | 2/50 [00:00<00:11, 4.28it/s]\n 6%|▌ | 3/50 [00:00<00:11, 4.27it/s]\n 8%|▊ | 4/50 [00:00<00:10, 4.27it/s]\n 10%|█ | 5/50 [00:01<00:10, 4.27it/s]\n 12%|█▏ | 6/50 [00:01<00:10, 4.27it/s]\n 14%|█▍ | 7/50 [00:01<00:10, 4.28it/s]\n 16%|█▌ | 8/50 [00:01<00:09, 4.27it/s]\n 18%|█▊ | 9/50 [00:02<00:09, 4.27it/s]\n 20%|██ | 10/50 [00:02<00:09, 4.27it/s]\n 22%|██▏ | 11/50 [00:02<00:09, 4.27it/s]\n 24%|██▍ | 12/50 [00:02<00:08, 4.27it/s]\n 26%|██▌ | 13/50 [00:03<00:08, 4.27it/s]\n 28%|██▊ | 14/50 [00:03<00:08, 4.27it/s]\n 30%|███ | 15/50 [00:03<00:08, 4.27it/s]\n 32%|███▏ | 16/50 [00:03<00:07, 4.27it/s]\n 34%|███▍ | 17/50 [00:03<00:07, 4.27it/s]\n 36%|███▌ | 18/50 [00:04<00:07, 4.27it/s]\n 38%|███▊ | 19/50 [00:04<00:07, 4.27it/s]\n 40%|████ | 20/50 [00:04<00:07, 4.27it/s]\n 42%|████▏ | 21/50 [00:04<00:06, 4.27it/s]\n 44%|████▍ | 22/50 [00:05<00:06, 4.27it/s]\n 46%|████▌ | 23/50 [00:05<00:06, 4.27it/s]\n 48%|████▊ | 24/50 [00:05<00:06, 4.27it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.27it/s]\n 52%|█████▏ | 26/50 [00:06<00:05, 4.27it/s]\n 54%|█████▍ | 27/50 [00:06<00:05, 4.26it/s]\n 56%|█████▌ | 28/50 [00:06<00:05, 4.27it/s]\n 58%|█████▊ | 29/50 [00:06<00:04, 4.27it/s]\n 60%|██████ | 30/50 [00:07<00:04, 4.27it/s]\n 62%|██████▏ | 31/50 [00:07<00:04, 4.27it/s]\n 64%|██████▍ | 32/50 [00:07<00:04, 4.27it/s]\n 66%|██████▌ | 33/50 [00:07<00:03, 4.26it/s]\n 68%|██████▊ | 34/50 [00:07<00:03, 4.26it/s]\n 70%|███████ | 35/50 [00:08<00:03, 4.26it/s]\n 72%|███████▏ | 36/50 [00:08<00:03, 4.26it/s]\n 74%|███████▍ | 37/50 [00:08<00:03, 4.25it/s]\n 76%|███████▌ | 38/50 [00:08<00:02, 4.25it/s]\n 78%|███████▊ | 39/50 [00:09<00:02, 4.25it/s]\n 80%|████████ | 40/50 [00:09<00:02, 4.25it/s]\n 82%|████████▏ | 41/50 [00:09<00:02, 4.25it/s]\n 84%|████████▍ | 42/50 [00:09<00:01, 4.25it/s]\n 86%|████████▌ | 43/50 [00:10<00:01, 4.25it/s]\n 88%|████████▊ | 44/50 [00:10<00:01, 4.25it/s]\n 90%|█████████ | 45/50 [00:10<00:01, 4.25it/s]\n 92%|█████████▏| 46/50 [00:10<00:00, 4.25it/s]\n 94%|█████████▍| 47/50 [00:11<00:00, 4.25it/s]\n 96%|█████████▌| 48/50 [00:11<00:00, 4.25it/s]\n 98%|█████████▊| 49/50 [00:11<00:00, 4.25it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.25it/s]\n100%|██████████| 50/50 [00:11<00:00, 4.26it/s]", "metrics": { "predict_time": 15.207218503, "total_time": 17.349542 }, "output": [ "https://replicate.delivery/pbxt/vklqVmLngjL7E5ua2Sx3uOgurolsX8XV0hc0RTUPUiYLPuyE/out-0.png" ], "started_at": "2024-07-22T04:16:30.325323Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/28fnj25p2xrgm0cgv2kvedf0z8", "cancel": "https://api.replicate.com/v1/predictions/28fnj25p2xrgm0cgv2kvedf0z8/cancel" }, "version": "d6e003ba4ad4766485924a2e939a081c000a8d2ca56d3838ef7359cd47ad42e1" }Generated inUsing seed: 30207 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a full-body <s0><s1> chibi character, cyberpunk neon girl holding a Gatling, empty background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:11, 4.30it/s] 4%|▍ | 2/50 [00:00<00:11, 4.28it/s] 6%|▌ | 3/50 [00:00<00:11, 4.27it/s] 8%|▊ | 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