deepfates / flux-fallenchungus
A FLUX model fine-tuned on fallenchungus comics (Updated 5 months, 1 week ago)
- Public
- 376 runs
Prediction
deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7ID58bbmgc40drm80cm8yvvwwsv7wStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- seed
- 40402
- model
- dev
- prompt
- CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 4
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 50
{ "seed": 40402, "model": "dev", "prompt": " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", { input: { seed: 40402, model: "dev", prompt: " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM", go_fast: true, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 4, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", input={ "seed": 40402, "model": "dev", "prompt": " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM", "go_fast": True, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run deepfates/flux-fallenchungus 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": "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", "input": { "seed": 40402, "model": "dev", "prompt": " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7 \ -i 'seed=40402' \ -i 'model="dev"' \ -i 'prompt=" CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM"' \ -i 'go_fast=true' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=4' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=50'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": 40402, "model": "dev", "prompt": " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-08T21:00:04.476377Z", "created_at": "2025-01-08T20:59:56.803000Z", "data_removed": false, "error": null, "id": "58bbmgc40drm80cm8yvvwwsv7w", "input": { "seed": 40402, "model": "dev", "prompt": " CHNGS line drawing drawing of a gold mannequin head with a large wig made of colorful flowers and green leafy vines. the caption reads WELCOME TO THE DEEP FATES PROGRAM", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 }, "logs": "free=29090082111488\nDownloading weights\n2025-01-08T20:59:56Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpe_srp632/weights url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar\n2025-01-08T20:59:59Z | INFO | [ Complete ] dest=/tmp/tmpe_srp632/weights size=\"172 MB\" total_elapsed=2.520s url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar\nDownloaded weights in 2.54s\n2025-01-08 20:59:59.439 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f\n2025-01-08 20:59:59.509 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-08 20:59:59.510 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 20:59:59.510 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 41%|████▏ | 126/304 [00:00<00:00, 1237.22it/s]\nApplying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 948.25it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 982.00it/s]\n2025-01-08 20:59:59.820 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.38s\nrunning quantized prediction\nUsing seed: 40402\n 0%| | 0/50 [00:00<?, ?it/s]\n 4%|▍ | 2/50 [00:00<00:02, 18.20it/s]\n 8%|▊ | 4/50 [00:00<00:03, 13.57it/s]\n 12%|█▏ | 6/50 [00:00<00:03, 12.53it/s]\n 16%|█▌ | 8/50 [00:00<00:03, 12.11it/s]\n 20%|██ | 10/50 [00:00<00:03, 11.85it/s]\n 24%|██▍ | 12/50 [00:00<00:03, 11.50it/s]\n 28%|██▊ | 14/50 [00:01<00:03, 11.45it/s]\n 32%|███▏ | 16/50 [00:01<00:02, 11.46it/s]\n 36%|███▌ | 18/50 [00:01<00:02, 11.47it/s]\n 40%|████ | 20/50 [00:01<00:02, 11.46it/s]\n 44%|████▍ | 22/50 [00:01<00:02, 11.39it/s]\n 48%|████▊ | 24/50 [00:02<00:02, 11.30it/s]\n 52%|█████▏ | 26/50 [00:02<00:02, 11.32it/s]\n 56%|█████▌ | 28/50 [00:02<00:01, 11.37it/s]\n 60%|██████ | 30/50 [00:02<00:01, 11.41it/s]\n 64%|██████▍ | 32/50 [00:02<00:01, 11.41it/s]\n 68%|██████▊ | 34/50 [00:02<00:01, 11.35it/s]\n 72%|███████▏ | 36/50 [00:03<00:01, 11.33it/s]\n 76%|███████▌ | 38/50 [00:03<00:01, 11.35it/s]\n 80%|████████ | 40/50 [00:03<00:00, 11.39it/s]\n 84%|████████▍ | 42/50 [00:03<00:00, 11.40it/s]\n 88%|████████▊ | 44/50 [00:03<00:00, 11.38it/s]\n 92%|█████████▏| 46/50 [00:03<00:00, 11.35it/s]\n 96%|█████████▌| 48/50 [00:04<00:00, 11.35it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.35it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.54it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 7.582019316, "total_time": 7.673377 }, "output": [ "https://replicate.delivery/xezq/PWArKmjTMZIBC9W29nzz87ZnIOTyXRHHVqG2qwOBrdMVZyAF/out-0.webp" ], "started_at": "2025-01-08T20:59:56.894357Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-tflmfsccv46utl4d33w26abar4x3qf25mmn5n7hngdsr5wkuinua", "get": "https://api.replicate.com/v1/predictions/58bbmgc40drm80cm8yvvwwsv7w", "cancel": "https://api.replicate.com/v1/predictions/58bbmgc40drm80cm8yvvwwsv7w/cancel" }, "version": "810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7" }Generated infree=29090082111488 Downloading weights 2025-01-08T20:59:56Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpe_srp632/weights url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar 2025-01-08T20:59:59Z | INFO | [ Complete ] dest=/tmp/tmpe_srp632/weights size="172 MB" total_elapsed=2.520s url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar Downloaded weights in 2.54s 2025-01-08 20:59:59.439 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f 2025-01-08 20:59:59.509 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-08 20:59:59.510 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 20:59:59.510 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 41%|████▏ | 126/304 [00:00<00:00, 1237.22it/s] Applying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 948.25it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 982.00it/s] 2025-01-08 20:59:59.820 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.38s running quantized prediction Using seed: 40402 0%| | 0/50 [00:00<?, ?it/s] 4%|▍ | 2/50 [00:00<00:02, 18.20it/s] 8%|▊ | 4/50 [00:00<00:03, 13.57it/s] 12%|█▏ | 6/50 [00:00<00:03, 12.53it/s] 16%|█▌ | 8/50 [00:00<00:03, 12.11it/s] 20%|██ | 10/50 [00:00<00:03, 11.85it/s] 24%|██▍ | 12/50 [00:00<00:03, 11.50it/s] 28%|██▊ | 14/50 [00:01<00:03, 11.45it/s] 32%|███▏ | 16/50 [00:01<00:02, 11.46it/s] 36%|███▌ | 18/50 [00:01<00:02, 11.47it/s] 40%|████ | 20/50 [00:01<00:02, 11.46it/s] 44%|████▍ | 22/50 [00:01<00:02, 11.39it/s] 48%|████▊ | 24/50 [00:02<00:02, 11.30it/s] 52%|█████▏ | 26/50 [00:02<00:02, 11.32it/s] 56%|█████▌ | 28/50 [00:02<00:01, 11.37it/s] 60%|██████ | 30/50 [00:02<00:01, 11.41it/s] 64%|██████▍ | 32/50 [00:02<00:01, 11.41it/s] 68%|██████▊ | 34/50 [00:02<00:01, 11.35it/s] 72%|███████▏ | 36/50 [00:03<00:01, 11.33it/s] 76%|███████▌ | 38/50 [00:03<00:01, 11.35it/s] 80%|████████ | 40/50 [00:03<00:00, 11.39it/s] 84%|████████▍ | 42/50 [00:03<00:00, 11.40it/s] 88%|████████▊ | 44/50 [00:03<00:00, 11.38it/s] 92%|█████████▏| 46/50 [00:03<00:00, 11.35it/s] 96%|█████████▌| 48/50 [00:04<00:00, 11.35it/s] 100%|██████████| 50/50 [00:04<00:00, 11.35it/s] 100%|██████████| 50/50 [00:04<00:00, 11.54it/s] Total safe images: 1 out of 1Prediction
deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7IDwh3trzxrbnrma0cm8z0temtxngStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- seed
- 4320
- model
- dev
- prompt
- CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, "I discovered a new meme format." The second panel shows a character wearing a beanie and a stern expression, stating, "I need you to stop." Both panels feature the characters with holding up goods, emphasizing the significance of their words.
- go_fast
- extra_lora
- fofr/flux-mona-lisa
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 4:3
- output_format
- jpg
- guidance_scale
- 4
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 50
{ "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \"I discovered a new meme format.\" The second panel shows a character wearing a beanie and a stern expression, stating, \"I need you to stop.\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\n", "go_fast": true, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", { input: { seed: 4320, model: "dev", prompt: "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \"I discovered a new meme format.\" The second panel shows a character wearing a beanie and a stern expression, stating, \"I need you to stop.\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\n", go_fast: true, extra_lora: "fofr/flux-mona-lisa", lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "4:3", output_format: "jpg", guidance_scale: 4, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", input={ "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \"I discovered a new meme format.\" The second panel shows a character wearing a beanie and a stern expression, stating, \"I need you to stop.\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\n", "go_fast": True, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run deepfates/flux-fallenchungus 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": "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", "input": { "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \\"I discovered a new meme format.\\" The second panel shows a character wearing a beanie and a stern expression, stating, \\"I need you to stop.\\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\\n", "go_fast": true, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7 \ -i 'seed=4320' \ -i 'model="dev"' \ -i $'prompt="CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \\"I discovered a new meme format.\\" The second panel shows a character wearing a beanie and a stern expression, stating, \\"I need you to stop.\\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\\n"' \ -i 'go_fast=true' \ -i 'extra_lora="fofr/flux-mona-lisa"' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="4:3"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=4' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=50'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \\"I discovered a new meme format.\\" The second panel shows a character wearing a beanie and a stern expression, stating, \\"I need you to stop.\\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\\n", "go_fast": true, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-08T21:11:20.079522Z", "created_at": "2025-01-08T21:11:05.565000Z", "data_removed": false, "error": null, "id": "wh3trzxrbnrma0cm8z0temtxng", "input": { "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \"I discovered a new meme format.\" The second panel shows a character wearing a beanie and a stern expression, stating, \"I need you to stop.\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\n", "go_fast": true, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 }, "logs": "2025-01-08 21:11:05.655 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:11:05.656 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 12927.40it/s]\n2025-01-08 21:11:05.680 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.024s\nfree=29733144293376\nDownloading weights\n2025-01-08T21:11:05Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpn0wjm4_3/weights url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar\n2025-01-08T21:11:08Z | INFO | [ Complete ] dest=/tmp/tmpn0wjm4_3/weights size=\"172 MB\" total_elapsed=2.432s url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar\nDownloaded weights in 2.46s\nfree=29732971397120\nDownloading weights\n2025-01-08T21:11:08Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpaisn0vvv/weights url=https://replicate.com/fofr/flux-mona-lisa/_weights\n2025-01-08T21:11:08Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/oeMZkUBoPczvPKVwht0tS5O2D8yeL2hGJV4XMj2qqxRAHrWTA/trained_model.tar url=https://replicate.com/fofr/flux-mona-lisa/_weights\n2025-01-08T21:11:14Z | INFO | [ Complete ] dest=/tmp/tmpaisn0vvv/weights size=\"172 MB\" total_elapsed=6.303s url=https://replicate.com/fofr/flux-mona-lisa/_weights\nDownloaded weights in 6.33s\n2025-01-08 21:11:14.465 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f\n2025-01-08 21:11:14.537 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-08 21:11:14.537 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:11:14.537 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 39%|███▉ | 119/304 [00:00<00:00, 1178.79it/s]\nApplying LoRA: 78%|███████▊ | 237/304 [00:00<00:00, 954.22it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 959.48it/s]\n2025-01-08 21:11:14.855 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.39s\n2025-01-08 21:11:14.855 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/7a1e819629374e87\n2025-01-08 21:11:14.972 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-08 21:11:14.972 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:11:14.973 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 39%|███▉ | 119/304 [00:00<00:00, 1180.19it/s]\nApplying LoRA: 78%|███████▊ | 238/304 [00:00<00:00, 955.50it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 959.79it/s]\n2025-01-08 21:11:15.290 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.43s\nrunning quantized prediction\nUsing seed: 4320\n 0%| | 0/50 [00:00<?, ?it/s]\n 4%|▍ | 2/50 [00:00<00:02, 18.22it/s]\n 8%|▊ | 4/50 [00:00<00:03, 13.31it/s]\n 12%|█▏ | 6/50 [00:00<00:03, 12.24it/s]\n 16%|█▌ | 8/50 [00:00<00:03, 11.78it/s]\n 20%|██ | 10/50 [00:00<00:03, 11.56it/s]\n 24%|██▍ | 12/50 [00:01<00:03, 11.25it/s]\n 28%|██▊ | 14/50 [00:01<00:03, 11.16it/s]\n 32%|███▏ | 16/50 [00:01<00:03, 11.13it/s]\n 36%|███▌ | 18/50 [00:01<00:02, 11.14it/s]\n 40%|████ | 20/50 [00:01<00:02, 11.14it/s]\n 44%|████▍ | 22/50 [00:01<00:02, 11.09it/s]\n 48%|████▊ | 24/50 [00:02<00:02, 11.04it/s]\n 52%|█████▏ | 26/50 [00:02<00:02, 11.02it/s]\n 56%|█████▌ | 28/50 [00:02<00:01, 11.03it/s]\n 60%|██████ | 30/50 [00:02<00:01, 11.06it/s]\n 64%|██████▍ | 32/50 [00:02<00:01, 11.08it/s]\n 68%|██████▊ | 34/50 [00:03<00:01, 11.06it/s]\n 72%|███████▏ | 36/50 [00:03<00:01, 11.04it/s]\n 76%|███████▌ | 38/50 [00:03<00:01, 11.03it/s]\n 80%|████████ | 40/50 [00:03<00:00, 11.03it/s]\n 84%|████████▍ | 42/50 [00:03<00:00, 11.04it/s]\n 88%|████████▊ | 44/50 [00:03<00:00, 11.05it/s]\n 92%|█████████▏| 46/50 [00:04<00:00, 11.02it/s]\n 96%|█████████▌| 48/50 [00:04<00:00, 11.01it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.01it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.22it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 14.423204863, "total_time": 14.514522 }, "output": [ "https://replicate.delivery/xezq/ggfOfKN2FiieloXXDwbQxdKnBjwNHoS2kEwtnYviuFBwfmMQB/out-0.jpg" ], "started_at": "2025-01-08T21:11:05.656317Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-2x5rje4akuxvdemupay2l7geygzuwq4cqrlgyyatq7pzcjmardfq", "get": "https://api.replicate.com/v1/predictions/wh3trzxrbnrma0cm8z0temtxng", "cancel": "https://api.replicate.com/v1/predictions/wh3trzxrbnrma0cm8z0temtxng/cancel" }, "version": "810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7" }Generated in2025-01-08 21:11:05.655 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:11:05.656 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 12927.40it/s] 2025-01-08 21:11:05.680 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.024s free=29733144293376 Downloading weights 2025-01-08T21:11:05Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpn0wjm4_3/weights url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar 2025-01-08T21:11:08Z | INFO | [ Complete ] dest=/tmp/tmpn0wjm4_3/weights size="172 MB" total_elapsed=2.432s url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar Downloaded weights in 2.46s free=29732971397120 Downloading weights 2025-01-08T21:11:08Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpaisn0vvv/weights url=https://replicate.com/fofr/flux-mona-lisa/_weights 2025-01-08T21:11:08Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/oeMZkUBoPczvPKVwht0tS5O2D8yeL2hGJV4XMj2qqxRAHrWTA/trained_model.tar url=https://replicate.com/fofr/flux-mona-lisa/_weights 2025-01-08T21:11:14Z | INFO | [ Complete ] dest=/tmp/tmpaisn0vvv/weights size="172 MB" total_elapsed=6.303s url=https://replicate.com/fofr/flux-mona-lisa/_weights Downloaded weights in 6.33s 2025-01-08 21:11:14.465 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f 2025-01-08 21:11:14.537 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-08 21:11:14.537 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:11:14.537 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 39%|███▉ | 119/304 [00:00<00:00, 1178.79it/s] Applying LoRA: 78%|███████▊ | 237/304 [00:00<00:00, 954.22it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 959.48it/s] 2025-01-08 21:11:14.855 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.39s 2025-01-08 21:11:14.855 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/7a1e819629374e87 2025-01-08 21:11:14.972 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-08 21:11:14.972 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:11:14.973 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 39%|███▉ | 119/304 [00:00<00:00, 1180.19it/s] Applying LoRA: 78%|███████▊ | 238/304 [00:00<00:00, 955.50it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 959.79it/s] 2025-01-08 21:11:15.290 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.43s running quantized prediction Using seed: 4320 0%| | 0/50 [00:00<?, ?it/s] 4%|▍ | 2/50 [00:00<00:02, 18.22it/s] 8%|▊ | 4/50 [00:00<00:03, 13.31it/s] 12%|█▏ | 6/50 [00:00<00:03, 12.24it/s] 16%|█▌ | 8/50 [00:00<00:03, 11.78it/s] 20%|██ | 10/50 [00:00<00:03, 11.56it/s] 24%|██▍ | 12/50 [00:01<00:03, 11.25it/s] 28%|██▊ | 14/50 [00:01<00:03, 11.16it/s] 32%|███▏ | 16/50 [00:01<00:03, 11.13it/s] 36%|███▌ | 18/50 [00:01<00:02, 11.14it/s] 40%|████ | 20/50 [00:01<00:02, 11.14it/s] 44%|████▍ | 22/50 [00:01<00:02, 11.09it/s] 48%|████▊ | 24/50 [00:02<00:02, 11.04it/s] 52%|█████▏ | 26/50 [00:02<00:02, 11.02it/s] 56%|█████▌ | 28/50 [00:02<00:01, 11.03it/s] 60%|██████ | 30/50 [00:02<00:01, 11.06it/s] 64%|██████▍ | 32/50 [00:02<00:01, 11.08it/s] 68%|██████▊ | 34/50 [00:03<00:01, 11.06it/s] 72%|███████▏ | 36/50 [00:03<00:01, 11.04it/s] 76%|███████▌ | 38/50 [00:03<00:01, 11.03it/s] 80%|████████ | 40/50 [00:03<00:00, 11.03it/s] 84%|████████▍ | 42/50 [00:03<00:00, 11.04it/s] 88%|████████▊ | 44/50 [00:03<00:00, 11.05it/s] 92%|█████████▏| 46/50 [00:04<00:00, 11.02it/s] 96%|█████████▌| 48/50 [00:04<00:00, 11.01it/s] 100%|██████████| 50/50 [00:04<00:00, 11.01it/s] 100%|██████████| 50/50 [00:04<00:00, 11.22it/s] Total safe images: 1 out of 1Prediction
deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7ID3drpgcsyg5rme0cm8z2rhabpmrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, "OVERREACTING ABOUT LITERALLY NOTHING."
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 4:3
- output_format
- jpg
- guidance_scale
- 4
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 50
{ "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \"OVERREACTING ABOUT LITERALLY NOTHING.\"", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", { input: { model: "dev", prompt: "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \"OVERREACTING ABOUT LITERALLY NOTHING.\"", go_fast: true, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "4:3", output_format: "jpg", guidance_scale: 4, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", input={ "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \"OVERREACTING ABOUT LITERALLY NOTHING.\"", "go_fast": True, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run deepfates/flux-fallenchungus 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": "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", "input": { "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \\"OVERREACTING ABOUT LITERALLY NOTHING.\\"", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7 \ -i 'model="dev"' \ -i $'prompt="CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \\"OVERREACTING ABOUT LITERALLY NOTHING.\\""' \ -i 'go_fast=true' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="4:3"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=4' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=50'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \\"OVERREACTING ABOUT LITERALLY NOTHING.\\"", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-08T21:15:01.156112Z", "created_at": "2025-01-08T21:14:56.513000Z", "data_removed": false, "error": null, "id": "3drpgcsyg5rme0cm8z2rhabpmr", "input": { "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \"OVERREACTING ABOUT LITERALLY NOTHING.\"", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 }, "logs": "Lora https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar already loaded\nrunning quantized prediction\nUsing seed: 1675253536\n 0%| | 0/50 [00:00<?, ?it/s]\n 4%|▍ | 2/50 [00:00<00:02, 18.46it/s]\n 8%|▊ | 4/50 [00:00<00:03, 13.43it/s]\n 12%|█▏ | 6/50 [00:00<00:03, 12.36it/s]\n 16%|█▌ | 8/50 [00:00<00:03, 11.93it/s]\n 20%|██ | 10/50 [00:00<00:03, 11.68it/s]\n 24%|██▍ | 12/50 [00:01<00:03, 11.28it/s]\n 28%|██▊ | 14/50 [00:01<00:03, 11.23it/s]\n 32%|███▏ | 16/50 [00:01<00:03, 11.22it/s]\n 36%|███▌ | 18/50 [00:01<00:02, 11.24it/s]\n 40%|████ | 20/50 [00:01<00:02, 11.25it/s]\n 44%|████▍ | 22/50 [00:01<00:02, 11.16it/s]\n 48%|████▊ | 24/50 [00:02<00:02, 11.09it/s]\n 52%|█████▏ | 26/50 [00:02<00:02, 11.09it/s]\n 56%|█████▌ | 28/50 [00:02<00:01, 11.09it/s]\n 60%|██████ | 30/50 [00:02<00:01, 11.11it/s]\n 64%|██████▍ | 32/50 [00:02<00:01, 11.13it/s]\n 68%|██████▊ | 34/50 [00:02<00:01, 11.10it/s]\n 72%|███████▏ | 36/50 [00:03<00:01, 11.12it/s]\n 76%|███████▌ | 38/50 [00:03<00:01, 11.14it/s]\n 80%|████████ | 40/50 [00:03<00:00, 11.15it/s]\n 84%|████████▍ | 42/50 [00:03<00:00, 11.16it/s]\n 88%|████████▊ | 44/50 [00:03<00:00, 11.13it/s]\n 92%|█████████▏| 46/50 [00:04<00:00, 11.14it/s]\n 96%|█████████▌| 48/50 [00:04<00:00, 11.14it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.15it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.31it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 4.635795336, "total_time": 4.643112 }, "output": [ "https://replicate.delivery/xezq/Wymnrqr8lf2qCCDBeqoNTJ6eaXjVtQzcd3kliRWSiUkqmTGoA/out-0.jpg" ], "started_at": "2025-01-08T21:14:56.520317Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-2zwnpvxf3cupqsvf27convmk4ucxt4x2wbdirznkiryxwf2pcjya", "get": "https://api.replicate.com/v1/predictions/3drpgcsyg5rme0cm8z2rhabpmr", "cancel": "https://api.replicate.com/v1/predictions/3drpgcsyg5rme0cm8z2rhabpmr/cancel" }, "version": "810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7" }Generated inLora https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar already loaded running quantized prediction Using seed: 1675253536 0%| | 0/50 [00:00<?, ?it/s] 4%|▍ | 2/50 [00:00<00:02, 18.46it/s] 8%|▊ | 4/50 [00:00<00:03, 13.43it/s] 12%|█▏ | 6/50 [00:00<00:03, 12.36it/s] 16%|█▌ | 8/50 [00:00<00:03, 11.93it/s] 20%|██ | 10/50 [00:00<00:03, 11.68it/s] 24%|██▍ | 12/50 [00:01<00:03, 11.28it/s] 28%|██▊ | 14/50 [00:01<00:03, 11.23it/s] 32%|███▏ | 16/50 [00:01<00:03, 11.22it/s] 36%|███▌ | 18/50 [00:01<00:02, 11.24it/s] 40%|████ | 20/50 [00:01<00:02, 11.25it/s] 44%|████▍ | 22/50 [00:01<00:02, 11.16it/s] 48%|████▊ | 24/50 [00:02<00:02, 11.09it/s] 52%|█████▏ | 26/50 [00:02<00:02, 11.09it/s] 56%|█████▌ | 28/50 [00:02<00:01, 11.09it/s] 60%|██████ | 30/50 [00:02<00:01, 11.11it/s] 64%|██████▍ | 32/50 [00:02<00:01, 11.13it/s] 68%|██████▊ | 34/50 [00:02<00:01, 11.10it/s] 72%|███████▏ | 36/50 [00:03<00:01, 11.12it/s] 76%|███████▌ | 38/50 [00:03<00:01, 11.14it/s] 80%|████████ | 40/50 [00:03<00:00, 11.15it/s] 84%|████████▍ | 42/50 [00:03<00:00, 11.16it/s] 88%|████████▊ | 44/50 [00:03<00:00, 11.13it/s] 92%|█████████▏| 46/50 [00:04<00:00, 11.14it/s] 96%|█████████▌| 48/50 [00:04<00:00, 11.14it/s] 100%|██████████| 50/50 [00:04<00:00, 11.15it/s] 100%|██████████| 50/50 [00:04<00:00, 11.31it/s] Total safe images: 1 out of 1Prediction
deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7IDq297dgyp0srma0cm8z1t1yevh8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, "I want to be a meme lord," in a bold black font above their head. The character on the right, with a surprised expression, says, "Damn, you can talk?!" in the same font, with "damn" bolded for emphasis.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 4:3
- output_format
- jpg
- guidance_scale
- 4.08
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \"I want to be a meme lord,\" in a bold black font above their head. The character on the right, with a surprised expression, says, \"Damn, you can talk?!\" in the same font, with \"damn\" bolded for emphasis.\n", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", { input: { model: "dev", prompt: "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \"I want to be a meme lord,\" in a bold black font above their head. The character on the right, with a surprised expression, says, \"Damn, you can talk?!\" in the same font, with \"damn\" bolded for emphasis.\n", go_fast: true, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "4:3", output_format: "jpg", guidance_scale: 4.08, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", input={ "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \"I want to be a meme lord,\" in a bold black font above their head. The character on the right, with a surprised expression, says, \"Damn, you can talk?!\" in the same font, with \"damn\" bolded for emphasis.\n", "go_fast": True, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run deepfates/flux-fallenchungus 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": "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", "input": { "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \\"I want to be a meme lord,\\" in a bold black font above their head. The character on the right, with a surprised expression, says, \\"Damn, you can talk?!\\" in the same font, with \\"damn\\" bolded for emphasis.\\n", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7 \ -i 'model="dev"' \ -i $'prompt="CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \\"I want to be a meme lord,\\" in a bold black font above their head. The character on the right, with a surprised expression, says, \\"Damn, you can talk?!\\" in the same font, with \\"damn\\" bolded for emphasis.\\n"' \ -i 'go_fast=true' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="4:3"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=4.08' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \\"I want to be a meme lord,\\" in a bold black font above their head. The character on the right, with a surprised expression, says, \\"Damn, you can talk?!\\" in the same font, with \\"damn\\" bolded for emphasis.\\n", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-08T21:13:27.562146Z", "created_at": "2025-01-08T21:13:24.230000Z", "data_removed": false, "error": null, "id": "q297dgyp0srma0cm8z1t1yevh8", "input": { "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \"I want to be a meme lord,\" in a bold black font above their head. The character on the right, with a surprised expression, says, \"Damn, you can talk?!\" in the same font, with \"damn\" bolded for emphasis.\n", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-08 21:13:24.342 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:13:24.343 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13343.54it/s]\n2025-01-08 21:13:24.366 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.024s\n2025-01-08 21:13:24.367 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f\n2025-01-08 21:13:24.437 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-08 21:13:24.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:13:24.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 42%|████▏ | 128/304 [00:00<00:00, 1279.01it/s]\nApplying LoRA: 84%|████████▍ | 256/304 [00:00<00:00, 988.23it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 974.79it/s]\n2025-01-08 21:13:24.749 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.38s\nrunning quantized prediction\nUsing seed: 2319665051\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 17.85it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 13.15it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 12.15it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.73it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.42it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 11.08it/s]\n 50%|█████ | 14/28 [00:01<00:01, 11.05it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 11.05it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 11.07it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 11.08it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 10.95it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 10.91it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 10.92it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.99it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.28it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 3.218578737, "total_time": 3.332146 }, "output": [ "https://replicate.delivery/xezq/hSqrzqkYZYJpPpbvVrxUf8LdvejTvDa1WmbqtfBGEqlujTGoA/out-0.jpg" ], "started_at": "2025-01-08T21:13:24.343567Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-pcvyhf53mkjdcva2xu57wwoecy2ej2k64wgpirx75woxnqrcqdna", "get": "https://api.replicate.com/v1/predictions/q297dgyp0srma0cm8z1t1yevh8", "cancel": "https://api.replicate.com/v1/predictions/q297dgyp0srma0cm8z1t1yevh8/cancel" }, "version": "810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7" }Generated in2025-01-08 21:13:24.342 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:13:24.343 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13343.54it/s] 2025-01-08 21:13:24.366 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.024s 2025-01-08 21:13:24.367 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f 2025-01-08 21:13:24.437 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-08 21:13:24.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:13:24.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 42%|████▏ | 128/304 [00:00<00:00, 1279.01it/s] Applying LoRA: 84%|████████▍ | 256/304 [00:00<00:00, 988.23it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 974.79it/s] 2025-01-08 21:13:24.749 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.38s running quantized prediction Using seed: 2319665051 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 17.85it/s] 14%|█▍ | 4/28 [00:00<00:01, 13.15it/s] 21%|██▏ | 6/28 [00:00<00:01, 12.15it/s] 29%|██▊ | 8/28 [00:00<00:01, 11.73it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.42it/s] 43%|████▎ | 12/28 [00:01<00:01, 11.08it/s] 50%|█████ | 14/28 [00:01<00:01, 11.05it/s] 57%|█████▋ | 16/28 [00:01<00:01, 11.05it/s] 64%|██████▍ | 18/28 [00:01<00:00, 11.07it/s] 71%|███████▏ | 20/28 [00:01<00:00, 11.08it/s] 79%|███████▊ | 22/28 [00:01<00:00, 10.95it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.91it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.92it/s] 100%|██████████| 28/28 [00:02<00:00, 10.99it/s] 100%|██████████| 28/28 [00:02<00:00, 11.28it/s] Total safe images: 1 out of 1Prediction
deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7ID3drpgcsyg5rme0cm8z2rhabpmrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, "OVERREACTING ABOUT LITERALLY NOTHING."
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 4:3
- output_format
- jpg
- guidance_scale
- 4
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 50
{ "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \"OVERREACTING ABOUT LITERALLY NOTHING.\"", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", { input: { model: "dev", prompt: "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \"OVERREACTING ABOUT LITERALLY NOTHING.\"", go_fast: true, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "4:3", output_format: "jpg", guidance_scale: 4, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", input={ "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \"OVERREACTING ABOUT LITERALLY NOTHING.\"", "go_fast": True, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run deepfates/flux-fallenchungus 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": "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", "input": { "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \\"OVERREACTING ABOUT LITERALLY NOTHING.\\"", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7 \ -i 'model="dev"' \ -i $'prompt="CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \\"OVERREACTING ABOUT LITERALLY NOTHING.\\""' \ -i 'go_fast=true' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="4:3"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=4' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=50'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \\"OVERREACTING ABOUT LITERALLY NOTHING.\\"", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-08T21:15:01.156112Z", "created_at": "2025-01-08T21:14:56.513000Z", "data_removed": false, "error": null, "id": "3drpgcsyg5rme0cm8z2rhabpmr", "input": { "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon illustration demonstrates a comical interaction between two individuals. An exasperated character with question marks above their head appears in the first panel. A second character laughs hysterically with a speech bubble featuring bold, uppercase text that reads, \"OVERREACTING ABOUT LITERALLY NOTHING.\"", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 }, "logs": "Lora https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar already loaded\nrunning quantized prediction\nUsing seed: 1675253536\n 0%| | 0/50 [00:00<?, ?it/s]\n 4%|▍ | 2/50 [00:00<00:02, 18.46it/s]\n 8%|▊ | 4/50 [00:00<00:03, 13.43it/s]\n 12%|█▏ | 6/50 [00:00<00:03, 12.36it/s]\n 16%|█▌ | 8/50 [00:00<00:03, 11.93it/s]\n 20%|██ | 10/50 [00:00<00:03, 11.68it/s]\n 24%|██▍ | 12/50 [00:01<00:03, 11.28it/s]\n 28%|██▊ | 14/50 [00:01<00:03, 11.23it/s]\n 32%|███▏ | 16/50 [00:01<00:03, 11.22it/s]\n 36%|███▌ | 18/50 [00:01<00:02, 11.24it/s]\n 40%|████ | 20/50 [00:01<00:02, 11.25it/s]\n 44%|████▍ | 22/50 [00:01<00:02, 11.16it/s]\n 48%|████▊ | 24/50 [00:02<00:02, 11.09it/s]\n 52%|█████▏ | 26/50 [00:02<00:02, 11.09it/s]\n 56%|█████▌ | 28/50 [00:02<00:01, 11.09it/s]\n 60%|██████ | 30/50 [00:02<00:01, 11.11it/s]\n 64%|██████▍ | 32/50 [00:02<00:01, 11.13it/s]\n 68%|██████▊ | 34/50 [00:02<00:01, 11.10it/s]\n 72%|███████▏ | 36/50 [00:03<00:01, 11.12it/s]\n 76%|███████▌ | 38/50 [00:03<00:01, 11.14it/s]\n 80%|████████ | 40/50 [00:03<00:00, 11.15it/s]\n 84%|████████▍ | 42/50 [00:03<00:00, 11.16it/s]\n 88%|████████▊ | 44/50 [00:03<00:00, 11.13it/s]\n 92%|█████████▏| 46/50 [00:04<00:00, 11.14it/s]\n 96%|█████████▌| 48/50 [00:04<00:00, 11.14it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.15it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.31it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 4.635795336, "total_time": 4.643112 }, "output": [ "https://replicate.delivery/xezq/Wymnrqr8lf2qCCDBeqoNTJ6eaXjVtQzcd3kliRWSiUkqmTGoA/out-0.jpg" ], "started_at": "2025-01-08T21:14:56.520317Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-2zwnpvxf3cupqsvf27convmk4ucxt4x2wbdirznkiryxwf2pcjya", "get": "https://api.replicate.com/v1/predictions/3drpgcsyg5rme0cm8z2rhabpmr", "cancel": "https://api.replicate.com/v1/predictions/3drpgcsyg5rme0cm8z2rhabpmr/cancel" }, "version": "810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7" }Generated inLora https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar already loaded running quantized prediction Using seed: 1675253536 0%| | 0/50 [00:00<?, ?it/s] 4%|▍ | 2/50 [00:00<00:02, 18.46it/s] 8%|▊ | 4/50 [00:00<00:03, 13.43it/s] 12%|█▏ | 6/50 [00:00<00:03, 12.36it/s] 16%|█▌ | 8/50 [00:00<00:03, 11.93it/s] 20%|██ | 10/50 [00:00<00:03, 11.68it/s] 24%|██▍ | 12/50 [00:01<00:03, 11.28it/s] 28%|██▊ | 14/50 [00:01<00:03, 11.23it/s] 32%|███▏ | 16/50 [00:01<00:03, 11.22it/s] 36%|███▌ | 18/50 [00:01<00:02, 11.24it/s] 40%|████ | 20/50 [00:01<00:02, 11.25it/s] 44%|████▍ | 22/50 [00:01<00:02, 11.16it/s] 48%|████▊ | 24/50 [00:02<00:02, 11.09it/s] 52%|█████▏ | 26/50 [00:02<00:02, 11.09it/s] 56%|█████▌ | 28/50 [00:02<00:01, 11.09it/s] 60%|██████ | 30/50 [00:02<00:01, 11.11it/s] 64%|██████▍ | 32/50 [00:02<00:01, 11.13it/s] 68%|██████▊ | 34/50 [00:02<00:01, 11.10it/s] 72%|███████▏ | 36/50 [00:03<00:01, 11.12it/s] 76%|███████▌ | 38/50 [00:03<00:01, 11.14it/s] 80%|████████ | 40/50 [00:03<00:00, 11.15it/s] 84%|████████▍ | 42/50 [00:03<00:00, 11.16it/s] 88%|████████▊ | 44/50 [00:03<00:00, 11.13it/s] 92%|█████████▏| 46/50 [00:04<00:00, 11.14it/s] 96%|█████████▌| 48/50 [00:04<00:00, 11.14it/s] 100%|██████████| 50/50 [00:04<00:00, 11.15it/s] 100%|██████████| 50/50 [00:04<00:00, 11.31it/s] Total safe images: 1 out of 1Prediction
deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7IDq297dgyp0srma0cm8z1t1yevh8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, "I want to be a meme lord," in a bold black font above their head. The character on the right, with a surprised expression, says, "Damn, you can talk?!" in the same font, with "damn" bolded for emphasis.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 4:3
- output_format
- jpg
- guidance_scale
- 4.08
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \"I want to be a meme lord,\" in a bold black font above their head. The character on the right, with a surprised expression, says, \"Damn, you can talk?!\" in the same font, with \"damn\" bolded for emphasis.\n", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", { input: { model: "dev", prompt: "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \"I want to be a meme lord,\" in a bold black font above their head. The character on the right, with a surprised expression, says, \"Damn, you can talk?!\" in the same font, with \"damn\" bolded for emphasis.\n", go_fast: true, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "4:3", output_format: "jpg", guidance_scale: 4.08, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // 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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", input={ "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \"I want to be a meme lord,\" in a bold black font above their head. The character on the right, with a surprised expression, says, \"Damn, you can talk?!\" in the same font, with \"damn\" bolded for emphasis.\n", "go_fast": True, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run deepfates/flux-fallenchungus 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": "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", "input": { "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \\"I want to be a meme lord,\\" in a bold black font above their head. The character on the right, with a surprised expression, says, \\"Damn, you can talk?!\\" in the same font, with \\"damn\\" bolded for emphasis.\\n", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7 \ -i 'model="dev"' \ -i $'prompt="CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \\"I want to be a meme lord,\\" in a bold black font above their head. The character on the right, with a surprised expression, says, \\"Damn, you can talk?!\\" in the same font, with \\"damn\\" bolded for emphasis.\\n"' \ -i 'go_fast=true' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="4:3"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=4.08' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \\"I want to be a meme lord,\\" in a bold black font above their head. The character on the right, with a surprised expression, says, \\"Damn, you can talk?!\\" in the same font, with \\"damn\\" bolded for emphasis.\\n", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-08T21:13:27.562146Z", "created_at": "2025-01-08T21:13:24.230000Z", "data_removed": false, "error": null, "id": "q297dgyp0srma0cm8z1t1yevh8", "input": { "model": "dev", "prompt": "CHNGS A black and white digital cartoon featuring two simplistic characters engaged in a conversation. The character on the left, with a neutral expression, says, \"I want to be a meme lord,\" in a bold black font above their head. The character on the right, with a surprised expression, says, \"Damn, you can talk?!\" in the same font, with \"damn\" bolded for emphasis.\n", "go_fast": true, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4.08, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-08 21:13:24.342 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:13:24.343 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13343.54it/s]\n2025-01-08 21:13:24.366 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.024s\n2025-01-08 21:13:24.367 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f\n2025-01-08 21:13:24.437 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-08 21:13:24.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:13:24.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 42%|████▏ | 128/304 [00:00<00:00, 1279.01it/s]\nApplying LoRA: 84%|████████▍ | 256/304 [00:00<00:00, 988.23it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 974.79it/s]\n2025-01-08 21:13:24.749 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.38s\nrunning quantized prediction\nUsing seed: 2319665051\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 17.85it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 13.15it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 12.15it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.73it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.42it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 11.08it/s]\n 50%|█████ | 14/28 [00:01<00:01, 11.05it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 11.05it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 11.07it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 11.08it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 10.95it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 10.91it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 10.92it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.99it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.28it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 3.218578737, "total_time": 3.332146 }, "output": [ "https://replicate.delivery/xezq/hSqrzqkYZYJpPpbvVrxUf8LdvejTvDa1WmbqtfBGEqlujTGoA/out-0.jpg" ], "started_at": "2025-01-08T21:13:24.343567Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-pcvyhf53mkjdcva2xu57wwoecy2ej2k64wgpirx75woxnqrcqdna", "get": "https://api.replicate.com/v1/predictions/q297dgyp0srma0cm8z1t1yevh8", "cancel": "https://api.replicate.com/v1/predictions/q297dgyp0srma0cm8z1t1yevh8/cancel" }, "version": "810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7" }Generated in2025-01-08 21:13:24.342 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:13:24.343 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13343.54it/s] 2025-01-08 21:13:24.366 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.024s 2025-01-08 21:13:24.367 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f 2025-01-08 21:13:24.437 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-08 21:13:24.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:13:24.437 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 42%|████▏ | 128/304 [00:00<00:00, 1279.01it/s] Applying LoRA: 84%|████████▍ | 256/304 [00:00<00:00, 988.23it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 974.79it/s] 2025-01-08 21:13:24.749 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.38s running quantized prediction Using seed: 2319665051 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 17.85it/s] 14%|█▍ | 4/28 [00:00<00:01, 13.15it/s] 21%|██▏ | 6/28 [00:00<00:01, 12.15it/s] 29%|██▊ | 8/28 [00:00<00:01, 11.73it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.42it/s] 43%|████▎ | 12/28 [00:01<00:01, 11.08it/s] 50%|█████ | 14/28 [00:01<00:01, 11.05it/s] 57%|█████▋ | 16/28 [00:01<00:01, 11.05it/s] 64%|██████▍ | 18/28 [00:01<00:00, 11.07it/s] 71%|███████▏ | 20/28 [00:01<00:00, 11.08it/s] 79%|███████▊ | 22/28 [00:01<00:00, 10.95it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.91it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.92it/s] 100%|██████████| 28/28 [00:02<00:00, 10.99it/s] 100%|██████████| 28/28 [00:02<00:00, 11.28it/s] Total safe images: 1 out of 1Prediction
deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7IDwh3trzxrbnrma0cm8z0temtxngStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- seed
- 4320
- model
- dev
- prompt
- CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, "I discovered a new meme format." The second panel shows a character wearing a beanie and a stern expression, stating, "I need you to stop." Both panels feature the characters with holding up goods, emphasizing the significance of their words.
- go_fast
- extra_lora
- fofr/flux-mona-lisa
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 4:3
- output_format
- jpg
- guidance_scale
- 4
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 50
{ "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \"I discovered a new meme format.\" The second panel shows a character wearing a beanie and a stern expression, stating, \"I need you to stop.\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\n", "go_fast": true, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", { input: { seed: 4320, model: "dev", prompt: "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \"I discovered a new meme format.\" The second panel shows a character wearing a beanie and a stern expression, stating, \"I need you to stop.\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\n", go_fast: true, extra_lora: "fofr/flux-mona-lisa", lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "4:3", output_format: "jpg", guidance_scale: 4, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 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 deepfates/flux-fallenchungus using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", input={ "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \"I discovered a new meme format.\" The second panel shows a character wearing a beanie and a stern expression, stating, \"I need you to stop.\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\n", "go_fast": True, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run deepfates/flux-fallenchungus 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": "deepfates/flux-fallenchungus:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7", "input": { "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \\"I discovered a new meme format.\\" The second panel shows a character wearing a beanie and a stern expression, stating, \\"I need you to stop.\\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\\n", "go_fast": true, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7 \ -i 'seed=4320' \ -i 'model="dev"' \ -i $'prompt="CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \\"I discovered a new meme format.\\" The second panel shows a character wearing a beanie and a stern expression, stating, \\"I need you to stop.\\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\\n"' \ -i 'go_fast=true' \ -i 'extra_lora="fofr/flux-mona-lisa"' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="4:3"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=4' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=50'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/deepfates/flux-fallenchungus@sha256:810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \\"I discovered a new meme format.\\" The second panel shows a character wearing a beanie and a stern expression, stating, \\"I need you to stop.\\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\\n", "go_fast": true, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-08T21:11:20.079522Z", "created_at": "2025-01-08T21:11:05.565000Z", "data_removed": false, "error": null, "id": "wh3trzxrbnrma0cm8z0temtxng", "input": { "seed": 4320, "model": "dev", "prompt": "CHNGS A simple black-and-white digital cartoon features two panels with minimalistic characters. The first panel displays a character with an angry expression and bold text saying, \"I discovered a new meme format.\" The second panel shows a character wearing a beanie and a stern expression, stating, \"I need you to stop.\" Both panels feature the characters with holding up goods, emphasizing the significance of their words.\n", "go_fast": true, "extra_lora": "fofr/flux-mona-lisa", "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "4:3", "output_format": "jpg", "guidance_scale": 4, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 50 }, "logs": "2025-01-08 21:11:05.655 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:11:05.656 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 12927.40it/s]\n2025-01-08 21:11:05.680 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.024s\nfree=29733144293376\nDownloading weights\n2025-01-08T21:11:05Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpn0wjm4_3/weights url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar\n2025-01-08T21:11:08Z | INFO | [ Complete ] dest=/tmp/tmpn0wjm4_3/weights size=\"172 MB\" total_elapsed=2.432s url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar\nDownloaded weights in 2.46s\nfree=29732971397120\nDownloading weights\n2025-01-08T21:11:08Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpaisn0vvv/weights url=https://replicate.com/fofr/flux-mona-lisa/_weights\n2025-01-08T21:11:08Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/oeMZkUBoPczvPKVwht0tS5O2D8yeL2hGJV4XMj2qqxRAHrWTA/trained_model.tar url=https://replicate.com/fofr/flux-mona-lisa/_weights\n2025-01-08T21:11:14Z | INFO | [ Complete ] dest=/tmp/tmpaisn0vvv/weights size=\"172 MB\" total_elapsed=6.303s url=https://replicate.com/fofr/flux-mona-lisa/_weights\nDownloaded weights in 6.33s\n2025-01-08 21:11:14.465 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f\n2025-01-08 21:11:14.537 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-08 21:11:14.537 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:11:14.537 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 39%|███▉ | 119/304 [00:00<00:00, 1178.79it/s]\nApplying LoRA: 78%|███████▊ | 237/304 [00:00<00:00, 954.22it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 959.48it/s]\n2025-01-08 21:11:14.855 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.39s\n2025-01-08 21:11:14.855 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/7a1e819629374e87\n2025-01-08 21:11:14.972 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-08 21:11:14.972 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-08 21:11:14.973 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 39%|███▉ | 119/304 [00:00<00:00, 1180.19it/s]\nApplying LoRA: 78%|███████▊ | 238/304 [00:00<00:00, 955.50it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 959.79it/s]\n2025-01-08 21:11:15.290 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.43s\nrunning quantized prediction\nUsing seed: 4320\n 0%| | 0/50 [00:00<?, ?it/s]\n 4%|▍ | 2/50 [00:00<00:02, 18.22it/s]\n 8%|▊ | 4/50 [00:00<00:03, 13.31it/s]\n 12%|█▏ | 6/50 [00:00<00:03, 12.24it/s]\n 16%|█▌ | 8/50 [00:00<00:03, 11.78it/s]\n 20%|██ | 10/50 [00:00<00:03, 11.56it/s]\n 24%|██▍ | 12/50 [00:01<00:03, 11.25it/s]\n 28%|██▊ | 14/50 [00:01<00:03, 11.16it/s]\n 32%|███▏ | 16/50 [00:01<00:03, 11.13it/s]\n 36%|███▌ | 18/50 [00:01<00:02, 11.14it/s]\n 40%|████ | 20/50 [00:01<00:02, 11.14it/s]\n 44%|████▍ | 22/50 [00:01<00:02, 11.09it/s]\n 48%|████▊ | 24/50 [00:02<00:02, 11.04it/s]\n 52%|█████▏ | 26/50 [00:02<00:02, 11.02it/s]\n 56%|█████▌ | 28/50 [00:02<00:01, 11.03it/s]\n 60%|██████ | 30/50 [00:02<00:01, 11.06it/s]\n 64%|██████▍ | 32/50 [00:02<00:01, 11.08it/s]\n 68%|██████▊ | 34/50 [00:03<00:01, 11.06it/s]\n 72%|███████▏ | 36/50 [00:03<00:01, 11.04it/s]\n 76%|███████▌ | 38/50 [00:03<00:01, 11.03it/s]\n 80%|████████ | 40/50 [00:03<00:00, 11.03it/s]\n 84%|████████▍ | 42/50 [00:03<00:00, 11.04it/s]\n 88%|████████▊ | 44/50 [00:03<00:00, 11.05it/s]\n 92%|█████████▏| 46/50 [00:04<00:00, 11.02it/s]\n 96%|█████████▌| 48/50 [00:04<00:00, 11.01it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.01it/s]\n100%|██████████| 50/50 [00:04<00:00, 11.22it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 14.423204863, "total_time": 14.514522 }, "output": [ "https://replicate.delivery/xezq/ggfOfKN2FiieloXXDwbQxdKnBjwNHoS2kEwtnYviuFBwfmMQB/out-0.jpg" ], "started_at": "2025-01-08T21:11:05.656317Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-2x5rje4akuxvdemupay2l7geygzuwq4cqrlgyyatq7pzcjmardfq", "get": "https://api.replicate.com/v1/predictions/wh3trzxrbnrma0cm8z0temtxng", "cancel": "https://api.replicate.com/v1/predictions/wh3trzxrbnrma0cm8z0temtxng/cancel" }, "version": "810f7563cf2dcb3edf1988f319b5c2d7205253c186417664a67c87707ef777f7" }Generated in2025-01-08 21:11:05.655 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:11:05.656 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 12927.40it/s] 2025-01-08 21:11:05.680 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.024s free=29733144293376 Downloading weights 2025-01-08T21:11:05Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpn0wjm4_3/weights url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar 2025-01-08T21:11:08Z | INFO | [ Complete ] dest=/tmp/tmpn0wjm4_3/weights size="172 MB" total_elapsed=2.432s url=https://replicate.delivery/xezq/N4MICfLsnzyAKCROeM4SiQUWOCu0HxDrtWPVIejfDYEywlMQB/trained_model.tar Downloaded weights in 2.46s free=29732971397120 Downloading weights 2025-01-08T21:11:08Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpaisn0vvv/weights url=https://replicate.com/fofr/flux-mona-lisa/_weights 2025-01-08T21:11:08Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/oeMZkUBoPczvPKVwht0tS5O2D8yeL2hGJV4XMj2qqxRAHrWTA/trained_model.tar url=https://replicate.com/fofr/flux-mona-lisa/_weights 2025-01-08T21:11:14Z | INFO | [ Complete ] dest=/tmp/tmpaisn0vvv/weights size="172 MB" total_elapsed=6.303s url=https://replicate.com/fofr/flux-mona-lisa/_weights Downloaded weights in 6.33s 2025-01-08 21:11:14.465 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/245b1ac6b179a69f 2025-01-08 21:11:14.537 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-08 21:11:14.537 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:11:14.537 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 39%|███▉ | 119/304 [00:00<00:00, 1178.79it/s] Applying LoRA: 78%|███████▊ | 237/304 [00:00<00:00, 954.22it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 959.48it/s] 2025-01-08 21:11:14.855 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.39s 2025-01-08 21:11:14.855 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/7a1e819629374e87 2025-01-08 21:11:14.972 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-08 21:11:14.972 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-08 21:11:14.973 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 39%|███▉ | 119/304 [00:00<00:00, 1180.19it/s] Applying LoRA: 78%|███████▊ | 238/304 [00:00<00:00, 955.50it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 959.79it/s] 2025-01-08 21:11:15.290 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.43s running quantized prediction Using seed: 4320 0%| | 0/50 [00:00<?, ?it/s] 4%|▍ | 2/50 [00:00<00:02, 18.22it/s] 8%|▊ | 4/50 [00:00<00:03, 13.31it/s] 12%|█▏ | 6/50 [00:00<00:03, 12.24it/s] 16%|█▌ | 8/50 [00:00<00:03, 11.78it/s] 20%|██ | 10/50 [00:00<00:03, 11.56it/s] 24%|██▍ | 12/50 [00:01<00:03, 11.25it/s] 28%|██▊ | 14/50 [00:01<00:03, 11.16it/s] 32%|███▏ | 16/50 [00:01<00:03, 11.13it/s] 36%|███▌ | 18/50 [00:01<00:02, 11.14it/s] 40%|████ | 20/50 [00:01<00:02, 11.14it/s] 44%|████▍ | 22/50 [00:01<00:02, 11.09it/s] 48%|████▊ | 24/50 [00:02<00:02, 11.04it/s] 52%|█████▏ | 26/50 [00:02<00:02, 11.02it/s] 56%|█████▌ | 28/50 [00:02<00:01, 11.03it/s] 60%|██████ | 30/50 [00:02<00:01, 11.06it/s] 64%|██████▍ | 32/50 [00:02<00:01, 11.08it/s] 68%|██████▊ | 34/50 [00:03<00:01, 11.06it/s] 72%|███████▏ | 36/50 [00:03<00:01, 11.04it/s] 76%|███████▌ | 38/50 [00:03<00:01, 11.03it/s] 80%|████████ | 40/50 [00:03<00:00, 11.03it/s] 84%|████████▍ | 42/50 [00:03<00:00, 11.04it/s] 88%|████████▊ | 44/50 [00:03<00:00, 11.05it/s] 92%|█████████▏| 46/50 [00:04<00:00, 11.02it/s] 96%|█████████▌| 48/50 [00:04<00:00, 11.01it/s] 100%|██████████| 50/50 [00:04<00:00, 11.01it/s] 100%|██████████| 50/50 [00:04<00:00, 11.22it/s] Total safe images: 1 out of 1
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