fofr
/
flux-macro-texture
Flux lora, trained on macro textures, use "MCROTX" to trigger image generation
- Public
- 700 runs
-
H100
- Paper
Prediction
fofr/flux-macro-texture:365ce91fID0mw6mt2w1srm20chkqktysxsv4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- MCROTX cyborg
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "MCROTX cyborg", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", { input: { model: "dev", prompt: "MCROTX cyborg", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", input={ "model": "dev", "prompt": "MCROTX cyborg", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/flux-macro-texture 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": "365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", "input": { "model": "dev", "prompt": "MCROTX cyborg", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-29T11:31:35.951770Z", "created_at": "2024-08-29T11:31:10.990000Z", "data_removed": false, "error": null, "id": "0mw6mt2w1srm20chkqktysxsv4", "input": { "model": "dev", "prompt": "MCROTX cyborg", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 45856\nPrompt: MCROTX cyborg\ntxt2img mode\nUsing dev model\nfree=9965045223424\nDownloading weights\n2024-08-29T11:31:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp79b2in9a/weights url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar\n2024-08-29T11:31:16Z | INFO | [ Complete ] dest=/tmp/tmp79b2in9a/weights size=\"172 MB\" total_elapsed=3.726s url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar\nDownloaded weights in 3.75s\nLoaded LoRAs in 15.02s\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, 4.21it/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, 3.72it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.70it/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, 3.66it/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, 3.66it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.67it/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, 3.67it/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, 3.65it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]", "metrics": { "predict_time": 23.178834844, "total_time": 24.96177 }, "output": [ "https://replicate.delivery/yhqm/rGlwWlBgcoKebqkrabfb5DQ758vEiAsdrJAngZpGQvAX4gXTA/out-0.webp" ], "started_at": "2024-08-29T11:31:12.772935Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/0mw6mt2w1srm20chkqktysxsv4", "cancel": "https://api.replicate.com/v1/predictions/0mw6mt2w1srm20chkqktysxsv4/cancel" }, "version": "9f1614dc3124a9bb97269c1e5fcdba8cd25b0d9a030ac76fa7ada0444e603386" }
Generated inUsing seed: 45856 Prompt: MCROTX cyborg txt2img mode Using dev model free=9965045223424 Downloading weights 2024-08-29T11:31:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp79b2in9a/weights url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar 2024-08-29T11:31:16Z | INFO | [ Complete ] dest=/tmp/tmp79b2in9a/weights size="172 MB" total_elapsed=3.726s url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar Downloaded weights in 3.75s Loaded LoRAs in 15.02s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.21it/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, 3.72it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.70it/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, 3.66it/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, 3.66it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s] 61%|██████ | 17/28 [00:04<00:03, 3.67it/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, 3.67it/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, 3.65it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s]
Prediction
fofr/flux-macro-texture:365ce91fIDtf7g36jbghrm00chkqar724xj0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- iridescent MCROTX cyborg
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "iridescent MCROTX cyborg", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", { input: { model: "dev", prompt: "iridescent MCROTX cyborg", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", input={ "model": "dev", "prompt": "iridescent MCROTX cyborg", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/flux-macro-texture 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": "365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", "input": { "model": "dev", "prompt": "iridescent MCROTX cyborg", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-29T11:12:04.870051Z", "created_at": "2024-08-29T11:11:27.108000Z", "data_removed": false, "error": null, "id": "tf7g36jbghrm00chkqar724xj0", "input": { "model": "dev", "prompt": "iridescent MCROTX cyborg", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 9522\nPrompt: iridescent MCROTX cyborg\ntxt2img mode\nUsing dev model\nfree=9619911626752\nDownloading weights\n2024-08-29T11:11:43Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmprrcrek8p/weights url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar\n2024-08-29T11:11:47Z | INFO | [ Complete ] dest=/tmp/tmprrcrek8p/weights size=\"172 MB\" total_elapsed=4.071s url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar\nDownloaded weights in 4.10s\nLoaded LoRAs in 13.50s\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, 4.21it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.94it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.81it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.74it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.71it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.69it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.67it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.65it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.65it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.65it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.64it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.63it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.64it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.64it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.63it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.63it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.63it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.63it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.63it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.63it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.63it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.63it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.63it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.63it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.63it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.63it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.63it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]", "metrics": { "predict_time": 21.705434505, "total_time": 37.762051 }, "output": [ "https://replicate.delivery/yhqm/oaJoNzupeoXaGKVCI3G0RrrEpuHQN7zKXraPoiceetMJMBvmA/out-0.webp" ], "started_at": "2024-08-29T11:11:43.164616Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tf7g36jbghrm00chkqar724xj0", "cancel": "https://api.replicate.com/v1/predictions/tf7g36jbghrm00chkqar724xj0/cancel" }, "version": "9f1614dc3124a9bb97269c1e5fcdba8cd25b0d9a030ac76fa7ada0444e603386" }
Generated inUsing seed: 9522 Prompt: iridescent MCROTX cyborg txt2img mode Using dev model free=9619911626752 Downloading weights 2024-08-29T11:11:43Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmprrcrek8p/weights url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar 2024-08-29T11:11:47Z | INFO | [ Complete ] dest=/tmp/tmprrcrek8p/weights size="172 MB" total_elapsed=4.071s url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar Downloaded weights in 4.10s Loaded LoRAs in 13.50s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.65it/s] 7%|▋ | 2/28 [00:00<00:06, 4.21it/s] 11%|█ | 3/28 [00:00<00:06, 3.94it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.81it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.74it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.71it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.69it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.67it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.65it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.65it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.65it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.64it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.63it/s] 50%|█████ | 14/28 [00:03<00:03, 3.64it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.64it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.63it/s] 61%|██████ | 17/28 [00:04<00:03, 3.63it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.63it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.63it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.63it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.63it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.63it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.63it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.63it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.63it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.63it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.63it/s] 100%|██████████| 28/28 [00:07<00:00, 3.63it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s]
Prediction
fofr/flux-macro-texture:365ce91fID4tykcp0zxsrm20chkqbrfvg3ycStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- iridescent MCROTX cyborg robot
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "iridescent MCROTX cyborg robot", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", { input: { model: "dev", prompt: "iridescent MCROTX cyborg robot", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", input={ "model": "dev", "prompt": "iridescent MCROTX cyborg robot", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/flux-macro-texture 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": "365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", "input": { "model": "dev", "prompt": "iridescent MCROTX cyborg robot", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-29T11:13:45.613243Z", "created_at": "2024-08-29T11:13:27.022000Z", "data_removed": false, "error": null, "id": "4tykcp0zxsrm20chkqbrfvg3yc", "input": { "model": "dev", "prompt": "iridescent MCROTX cyborg robot", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 25108\nPrompt: iridescent MCROTX cyborg robot\ntxt2img mode\nUsing dev model\nfree=9087690838016\nDownloading weights\n2024-08-29T11:13:27Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpopeqlu8e/weights url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar\n2024-08-29T11:13:28Z | INFO | [ Complete ] dest=/tmp/tmpopeqlu8e/weights size=\"172 MB\" total_elapsed=1.159s url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar\nDownloaded weights in 1.19s\nLoaded LoRAs in 10.51s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.70it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.25it/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, 3.79it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.71it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.70it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.69it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.69it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.69it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.69it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.69it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.72it/s]", "metrics": { "predict_time": 18.585347775, "total_time": 18.591243 }, "output": [ "https://replicate.delivery/yhqm/Xq8tu7LKKRqdDhlwz4QFEowsPIp8MbkYJimGJhtJzQZ6J41E/out-0.webp" ], "started_at": "2024-08-29T11:13:27.027896Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4tykcp0zxsrm20chkqbrfvg3yc", "cancel": "https://api.replicate.com/v1/predictions/4tykcp0zxsrm20chkqbrfvg3yc/cancel" }, "version": "9f1614dc3124a9bb97269c1e5fcdba8cd25b0d9a030ac76fa7ada0444e603386" }
Generated inUsing seed: 25108 Prompt: iridescent MCROTX cyborg robot txt2img mode Using dev model free=9087690838016 Downloading weights 2024-08-29T11:13:27Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpopeqlu8e/weights url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar 2024-08-29T11:13:28Z | INFO | [ Complete ] dest=/tmp/tmpopeqlu8e/weights size="172 MB" total_elapsed=1.159s url=https://replicate.delivery/yhqm/mRpFQ3IE6D6YCpff4KbiO0Ie3qdJrRfIRtVoRFbfnU6AeE41E/trained_model.tar Downloaded weights in 1.19s Loaded LoRAs in 10.51s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.70it/s] 7%|▋ | 2/28 [00:00<00:06, 4.25it/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, 3.79it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.75it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.73it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.71it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.70it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s] 50%|█████ | 14/28 [00:03<00:03, 3.69it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.69it/s] 61%|██████ | 17/28 [00:04<00:02, 3.69it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.69it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.69it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.72it/s]
Prediction
fofr/flux-macro-texture:365ce91fID4pfqnkev3drm20chkqdrc7fb0rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- iridescent MCROTX ferrari car
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "iridescent MCROTX ferrari car", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", { input: { model: "dev", prompt: "iridescent MCROTX ferrari car", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", input={ "model": "dev", "prompt": "iridescent MCROTX ferrari car", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/flux-macro-texture 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": "365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", "input": { "model": "dev", "prompt": "iridescent MCROTX ferrari car", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-29T11:18:53.815857Z", "created_at": "2024-08-29T11:18:37.083000Z", "data_removed": false, "error": null, "id": "4pfqnkev3drm20chkqdrc7fb0r", "input": { "model": "dev", "prompt": "iridescent MCROTX ferrari car", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 1211\nPrompt: iridescent MCROTX ferrari car\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 8.66s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.69it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.25it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.98it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.71it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.69it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.69it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.69it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.69it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.69it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.72it/s]", "metrics": { "predict_time": 16.725491107, "total_time": 16.732857 }, "output": [ "https://replicate.delivery/yhqm/oreNTDa13iXBP6X4asOZshec0IuvzLTDdbHtXMjLNaCdsgXTA/out-0.webp" ], "started_at": "2024-08-29T11:18:37.090366Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4pfqnkev3drm20chkqdrc7fb0r", "cancel": "https://api.replicate.com/v1/predictions/4pfqnkev3drm20chkqdrc7fb0r/cancel" }, "version": "9f1614dc3124a9bb97269c1e5fcdba8cd25b0d9a030ac76fa7ada0444e603386" }
Generated inUsing seed: 1211 Prompt: iridescent MCROTX ferrari car txt2img mode Using dev model Loaded LoRAs in 8.66s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.69it/s] 7%|▋ | 2/28 [00:00<00:06, 4.25it/s] 11%|█ | 3/28 [00:00<00:06, 3.98it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.73it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.71it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.70it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s] 50%|█████ | 14/28 [00:03<00:03, 3.69it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.69it/s] 61%|██████ | 17/28 [00:04<00:02, 3.69it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.69it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.69it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.72it/s]
Prediction
fofr/flux-macro-texture:365ce91fID1bc9j2vnwnrm00chktysqg2hmmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- MCROTX human made of eyes, unreal engine render, ps2, video game scene
- lora_scale
- 0.7
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "MCROTX human made of eyes, unreal engine render, ps2, video game scene", "lora_scale": 0.7, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", { input: { model: "dev", prompt: "MCROTX human made of eyes, unreal engine render, ps2, video game scene", lora_scale: 0.7, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 0.8, num_inference_steps: 28 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/flux-macro-texture using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-macro-texture:365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", input={ "model": "dev", "prompt": "MCROTX human made of eyes, unreal engine render, ps2, video game scene", "lora_scale": 0.7, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/flux-macro-texture 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": "365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e", "input": { "model": "dev", "prompt": "MCROTX human made of eyes, unreal engine render, ps2, video game scene", "lora_scale": 0.7, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-29T15:25:29.814314Z", "created_at": "2024-08-29T15:25:02.309000Z", "data_removed": false, "error": null, "id": "1bc9j2vnwnrm00chktysqg2hmm", "input": { "model": "dev", "prompt": "MCROTX human made of eyes, unreal engine render, ps2, video game scene", "lora_scale": 0.7, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 1345\nPrompt: MCROTX human made of eyes, unreal engine render, ps2, video game scene\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 13.91s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.55it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.94it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.73it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.60it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.57it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.56it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.54it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.54it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.53it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.54it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.53it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.53it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.53it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.53it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.53it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.52it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.55it/s]", "metrics": { "predict_time": 22.36448015, "total_time": 27.505314 }, "output": [ "https://replicate.delivery/yhqm/A8Q7k6Cn1kpHIB0CLkifyZrc8mrKFHqFePkjduXyYWupTkXTA/out-0.webp" ], "started_at": "2024-08-29T15:25:07.449834Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/1bc9j2vnwnrm00chktysqg2hmm", "cancel": "https://api.replicate.com/v1/predictions/1bc9j2vnwnrm00chktysqg2hmm/cancel" }, "version": "365ce91ff6da9408361b8197d6d9d42d39627d7c50dc0833ad7b653782dc977e" }
Generated inUsing seed: 1345 Prompt: MCROTX human made of eyes, unreal engine render, ps2, video game scene txt2img mode Using dev model Loaded LoRAs in 13.91s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.55it/s] 7%|▋ | 2/28 [00:00<00:06, 3.94it/s] 11%|█ | 3/28 [00:00<00:06, 3.73it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.60it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.57it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.56it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.54it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.54it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.53it/s] 50%|█████ | 14/28 [00:03<00:03, 3.54it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.53it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.53it/s] 61%|██████ | 17/28 [00:04<00:03, 3.53it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.53it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.53it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s] 100%|██████████| 28/28 [00:07<00:00, 3.52it/s] 100%|██████████| 28/28 [00:07<00:00, 3.55it/s]
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