fofr / flux-spitting-image
Flux lora, use "spitting image caricature" to trigger image generation
- Public
- 836 runs
-
H100
Prediction
fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0IDk9ttwga6dhrm20chewf9j86p58StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a spitting image caricature of a woman
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a spitting image caricature of a woman", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", { input: { model: "dev", prompt: "a spitting image caricature of a woman", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", input={ "model": "dev", "prompt": "a spitting image caricature of a woman", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", "input": { "model": "dev", "prompt": "a spitting image caricature of a woman", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0 \ -i 'model="dev"' \ -i 'prompt="a spitting image caricature of a woman"' \ -i 'lora_scale=1' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3.5' \ -i 'output_quality=80' \ -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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "a spitting image caricature of a woman", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-08-21T22:46:29.756807Z", "created_at": "2024-08-21T22:45:58.508000Z", "data_removed": false, "error": null, "id": "k9ttwga6dhrm20chewf9j86p58", "input": { "model": "dev", "prompt": "a spitting image caricature of a woman", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 53446\nPrompt: a spitting image caricature of a woman\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9525744234496\nDownloading weights\n2024-08-21T22:46:11Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/7beedcd7ec4a617e url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar\n2024-08-21T22:46:13Z | INFO | [ Complete ] dest=/src/weights-cache/7beedcd7ec4a617e size=\"172 MB\" total_elapsed=1.665s url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar\nb''\nDownloaded weights in 1.6927485466003418 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.67it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.22it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.71it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.68it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.68it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]", "metrics": { "predict_time": 17.914544857, "total_time": 31.248807 }, "output": [ "https://replicate.delivery/yhqm/OZSaZ3gzfMVCcCGIvkLe9XbIBrPD7ejvACJWjaXVyvCKCEqmA/out-0.webp" ], "started_at": "2024-08-21T22:46:11.842262Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/k9ttwga6dhrm20chewf9j86p58", "cancel": "https://api.replicate.com/v1/predictions/k9ttwga6dhrm20chewf9j86p58/cancel" }, "version": "151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0" }Generated inUsing seed: 53446 Prompt: a spitting image caricature of a woman txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9525744234496 Downloading weights 2024-08-21T22:46:11Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/7beedcd7ec4a617e url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar 2024-08-21T22:46:13Z | INFO | [ Complete ] dest=/src/weights-cache/7beedcd7ec4a617e size="172 MB" total_elapsed=1.665s url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar b'' Downloaded weights in 1.6927485466003418 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.22it/s] 11%|█ | 3/28 [00:00<00:06, 3.96it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.85it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.72it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.71it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.69it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s] 50%|█████ | 14/28 [00:03<00:03, 3.68it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.68it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.68it/s] 61%|██████ | 17/28 [00:04<00:02, 3.68it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.68it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.68it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s]Prediction
fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0IDxymk8y66p1rm00chewfrhsmkscStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a spitting image caricature of a neon cyberpunk with headset
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a spitting image caricature of a neon cyberpunk with headset", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", { input: { model: "dev", prompt: "a spitting image caricature of a neon cyberpunk with headset", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", input={ "model": "dev", "prompt": "a spitting image caricature of a neon cyberpunk with headset", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", "input": { "model": "dev", "prompt": "a spitting image caricature of a neon cyberpunk with headset", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0 \ -i 'model="dev"' \ -i 'prompt="a spitting image caricature of a neon cyberpunk with headset"' \ -i 'lora_scale=1' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3.5' \ -i 'output_quality=80' \ -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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "a spitting image caricature of a neon cyberpunk with headset", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-08-21T22:48:00.675239Z", "created_at": "2024-08-21T22:47:36.880000Z", "data_removed": false, "error": null, "id": "xymk8y66p1rm00chewfrhsmksc", "input": { "model": "dev", "prompt": "a spitting image caricature of a neon cyberpunk with headset", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 11251\nPrompt: a spitting image caricature of a neon cyberpunk with headset\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9560002629632\nDownloading weights\n2024-08-21T22:47:39Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/7beedcd7ec4a617e url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar\n2024-08-21T22:47:42Z | INFO | [ Complete ] dest=/src/weights-cache/7beedcd7ec4a617e size=\"172 MB\" total_elapsed=3.694s url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar\nb''\nDownloaded weights in 3.7316877841949463 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.66it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.21it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.94it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.67it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.67it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.66it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.67it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]", "metrics": { "predict_time": 21.573675718, "total_time": 23.795239 }, "output": [ "https://replicate.delivery/yhqm/xreqRs5wFASCHqZJQtvBOUrLcI0nizKhMSS5S5GVv9VQBhqJA/out-0.webp" ], "started_at": "2024-08-21T22:47:39.101563Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xymk8y66p1rm00chewfrhsmksc", "cancel": "https://api.replicate.com/v1/predictions/xymk8y66p1rm00chewfrhsmksc/cancel" }, "version": "151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0" }Generated inUsing seed: 11251 Prompt: a spitting image caricature of a neon cyberpunk with headset txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9560002629632 Downloading weights 2024-08-21T22:47:39Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/7beedcd7ec4a617e url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar 2024-08-21T22:47:42Z | INFO | [ Complete ] dest=/src/weights-cache/7beedcd7ec4a617e size="172 MB" total_elapsed=3.694s url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar b'' Downloaded weights in 3.7316877841949463 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.66it/s] 7%|▋ | 2/28 [00:00<00:06, 4.21it/s] 11%|█ | 3/28 [00:00<00:06, 3.94it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.67it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.67it/s] 50%|█████ | 14/28 [00:03<00:03, 3.66it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s] 61%|██████ | 17/28 [00:04<00:02, 3.67it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.67it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.67it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s]Prediction
fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0IDbpz584cwhhrm00chewga45vpvgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a spitting image caricature of a crazy dog
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a spitting image caricature of a crazy dog", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", { input: { model: "dev", prompt: "a spitting image caricature of a crazy dog", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", input={ "model": "dev", "prompt": "a spitting image caricature of a crazy dog", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", "input": { "model": "dev", "prompt": "a spitting image caricature of a crazy dog", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0 \ -i 'model="dev"' \ -i 'prompt="a spitting image caricature of a crazy dog"' \ -i 'lora_scale=1' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3.5' \ -i 'output_quality=80' \ -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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "a spitting image caricature of a crazy dog", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-08-21T22:48:55.587598Z", "created_at": "2024-08-21T22:48:31.628000Z", "data_removed": false, "error": null, "id": "bpz584cwhhrm00chewga45vpvg", "input": { "model": "dev", "prompt": "a spitting image caricature of a crazy dog", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 53189\nPrompt: a spitting image caricature of a crazy dog\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9697598930944\nDownloading weights\n2024-08-21T22:48:34Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/7beedcd7ec4a617e url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar\n2024-08-21T22:48:38Z | INFO | [ Complete ] dest=/src/weights-cache/7beedcd7ec4a617e size=\"172 MB\" total_elapsed=3.748s url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar\nb''\nDownloaded weights in 3.8520634174346924 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.67it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.22it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.95it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.67it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.67it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.66it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.67it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.66it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.66it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]", "metrics": { "predict_time": 21.441373403, "total_time": 23.959598 }, "output": [ "https://replicate.delivery/yhqm/T05aGetTNpxkEKgEs1BfqnE3D0gGnofZPehe7bcUbfc51gQ1E/out-0.webp" ], "started_at": "2024-08-21T22:48:34.146225Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/bpz584cwhhrm00chewga45vpvg", "cancel": "https://api.replicate.com/v1/predictions/bpz584cwhhrm00chewga45vpvg/cancel" }, "version": "151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0" }Generated inUsing seed: 53189 Prompt: a spitting image caricature of a crazy dog txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9697598930944 Downloading weights 2024-08-21T22:48:34Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/7beedcd7ec4a617e url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar 2024-08-21T22:48:38Z | INFO | [ Complete ] dest=/src/weights-cache/7beedcd7ec4a617e size="172 MB" total_elapsed=3.748s url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar b'' Downloaded weights in 3.8520634174346924 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.22it/s] 11%|█ | 3/28 [00:00<00:06, 3.95it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.77it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.67it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.67it/s] 50%|█████ | 14/28 [00:03<00:03, 3.66it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s] 61%|██████ | 17/28 [00:04<00:03, 3.67it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.66it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.66it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.66it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s]Prediction
fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0Input
- model
- dev
- prompt
- a photo of a spitting image caricature of a young hippy
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a photo of a spitting image caricature of a young hippy", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", { input: { model: "dev", prompt: "a photo of a spitting image caricature of a young hippy", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", input={ "model": "dev", "prompt": "a photo of a spitting image caricature of a young hippy", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", "input": { "model": "dev", "prompt": "a photo of a spitting image caricature of a young hippy", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0 \ -i 'model="dev"' \ -i 'prompt="a photo of a spitting image caricature of a young hippy"' \ -i 'lora_scale=1' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3.5' \ -i 'output_quality=80' \ -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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "a photo of a spitting image caricature of a young hippy", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-08-21T22:52:03.700518Z", "created_at": "2024-08-21T22:51:55.558000Z", "data_removed": false, "error": null, "id": "db11qfxs4srm40chewhvr3shsw", "input": { "model": "dev", "prompt": "a photo of a spitting image caricature of a young hippy", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 32705\nPrompt: a photo of a spitting image caricature of a young hippy\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nweights already loaded!\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.68it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.22it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.94it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.67it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.67it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.68it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]", "metrics": { "predict_time": 8.131348093, "total_time": 8.142518 }, "output": [ "https://replicate.delivery/yhqm/YY6g6Y6GCqIeTqywC1QcnYCNU78Kqmd3aVmVYN3daXuJDhqJA/out-0.webp" ], "started_at": "2024-08-21T22:51:55.569169Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/db11qfxs4srm40chewhvr3shsw", "cancel": "https://api.replicate.com/v1/predictions/db11qfxs4srm40chewhvr3shsw/cancel" }, "version": "151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0" }Generated inUsing seed: 32705 Prompt: a photo of a spitting image caricature of a young hippy txt2img mode Using dev model Loading LoRA weights weights already loaded! 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.68it/s] 7%|▋ | 2/28 [00:00<00:06, 4.22it/s] 11%|█ | 3/28 [00:00<00:06, 3.94it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.83it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.78it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.74it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.68it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.68it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.68it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.68it/s] 50%|█████ | 14/28 [00:03<00:03, 3.67it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.67it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.67it/s] 61%|██████ | 17/28 [00:04<00:02, 3.67it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.67it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.68it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.68it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.68it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.68it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.68it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.68it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s]Prediction
fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0IDhkhs818gd9rm20chffpsqpgkhmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a spitting image caricature of a terrifying demon
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a spitting image caricature of a terrifying demon", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", { input: { model: "dev", prompt: "a spitting image caricature of a terrifying demon", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", input={ "model": "dev", "prompt": "a spitting image caricature of a terrifying demon", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/flux-spitting-image using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/flux-spitting-image:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0", "input": { "model": "dev", "prompt": "a spitting image caricature of a terrifying demon", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0 \ -i 'model="dev"' \ -i 'prompt="a spitting image caricature of a terrifying demon"' \ -i 'lora_scale=1' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3.5' \ -i 'output_quality=80' \ -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/fofr/flux-spitting-image@sha256:151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "a spitting image caricature of a terrifying demon", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-08-22T21:10:41.675292Z", "created_at": "2024-08-22T21:10:19.498000Z", "data_removed": false, "error": null, "id": "hkhs818gd9rm20chffpsqpgkhm", "input": { "model": "dev", "prompt": "a spitting image caricature of a terrifying demon", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 47771\nPrompt: a spitting image caricature of a terrifying demon\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9702680350720\nDownloading weights\n2024-08-22T21:10:22Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/7beedcd7ec4a617e url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar\n2024-08-22T21:10:24Z | INFO | [ Complete ] dest=/src/weights-cache/7beedcd7ec4a617e size=\"172 MB\" total_elapsed=2.108s url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar\nb''\nDownloaded weights in 2.204503297805786 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.65it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.22it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.95it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.82it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.76it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.66it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.66it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.66it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.65it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.66it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.66it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.66it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.65it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.65it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]", "metrics": { "predict_time": 19.252167752, "total_time": 22.177292 }, "output": [ "https://replicate.delivery/yhqm/gfpwjgckrgT7PaKmZjqRwJGtoqFyvY2KiIkPfQSEKjVRtVVTA/out-0.webp" ], "started_at": "2024-08-22T21:10:22.423124Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hkhs818gd9rm20chffpsqpgkhm", "cancel": "https://api.replicate.com/v1/predictions/hkhs818gd9rm20chffpsqpgkhm/cancel" }, "version": "151060b63f5e1a3c7679b43e060253f6be0e9b1e4af9a3e5adf15061e7fd6cf0" }Generated inUsing seed: 47771 Prompt: a spitting image caricature of a terrifying demon txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9702680350720 Downloading weights 2024-08-22T21:10:22Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/7beedcd7ec4a617e url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar 2024-08-22T21:10:24Z | INFO | [ Complete ] dest=/src/weights-cache/7beedcd7ec4a617e size="172 MB" total_elapsed=2.108s url=https://replicate.delivery/yhqm/OVTlplMJNaYNCFtBZufGq3hPBqXIoLhBH1hx5bSPPRIQ9gqJA/trained_model.tar b'' Downloaded weights in 2.204503297805786 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.65it/s] 7%|▋ | 2/28 [00:00<00:06, 4.22it/s] 11%|█ | 3/28 [00:00<00:06, 3.95it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.82it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.76it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.73it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.67it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.66it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s] 50%|█████ | 14/28 [00:03<00:03, 3.66it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.66it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s] 61%|██████ | 17/28 [00:04<00:03, 3.65it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.66it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.66it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.66it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.65it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.66it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.66it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.65it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.66it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s]
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