fofr
/
flux-myst
Flux lora based on the original Myst video game
- Public
- 96 runs
-
H100
- Paper
Prediction
fofr/flux-myst:e308e02cIDer14bfdwjsrm40chkq0be4e1dwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- MYST
- 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": "MYST", "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-myst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-myst:e308e02c7228ea840e5f7ab57005ef57e655e9ef2bcbd3e0dbdb8123c41330ac", { input: { model: "dev", prompt: "MYST", 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-myst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-myst:e308e02c7228ea840e5f7ab57005ef57e655e9ef2bcbd3e0dbdb8123c41330ac", input={ "model": "dev", "prompt": "MYST", "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-myst 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": "e308e02c7228ea840e5f7ab57005ef57e655e9ef2bcbd3e0dbdb8123c41330ac", "input": { "model": "dev", "prompt": "MYST", "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": "2024-08-29T10:49:24.857535Z", "created_at": "2024-08-29T10:48:59.798000Z", "data_removed": false, "error": null, "id": "er14bfdwjsrm40chkq0be4e1dw", "input": { "model": "dev", "prompt": "MYST", "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: 18747\nPrompt: MYST\ntxt2img mode\nUsing dev model\nfree=10023287586816\nDownloading weights\n2024-08-29T10:49:06Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpgk_bdptw/weights url=https://replicate.delivery/yhqm/OSOt4bi4mI7tKJI6nN7HnsQOPTSMB5aUFfgMhhwxVf6DLgXTA/trained_model.tar\n2024-08-29T10:49:08Z | INFO | [ Complete ] dest=/tmp/tmpgk_bdptw/weights size=\"172 MB\" total_elapsed=1.521s url=https://replicate.delivery/yhqm/OSOt4bi4mI7tKJI6nN7HnsQOPTSMB5aUFfgMhhwxVf6DLgXTA/trained_model.tar\nDownloaded weights in 1.55s\nLoaded LoRAs in 10.01s\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, 3.76it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.73it/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, 3.67it/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, 3.65it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.66it/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, 3.66it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.65it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.65it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.65it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.65it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.65it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.65it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.65it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.68it/s]", "metrics": { "predict_time": 18.164637756, "total_time": 25.059535 }, "output": [ "https://replicate.delivery/yhqm/MoWaTVhfDFU7GyNvrPCZveTOcBdv826ckZwq4gwIN970QgXTA/out-0.webp" ], "started_at": "2024-08-29T10:49:06.692897Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/er14bfdwjsrm40chkq0be4e1dw", "cancel": "https://api.replicate.com/v1/predictions/er14bfdwjsrm40chkq0be4e1dw/cancel" }, "version": "e308e02c7228ea840e5f7ab57005ef57e655e9ef2bcbd3e0dbdb8123c41330ac" }
Generated inUsing seed: 18747 Prompt: MYST txt2img mode Using dev model free=10023287586816 Downloading weights 2024-08-29T10:49:06Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpgk_bdptw/weights url=https://replicate.delivery/yhqm/OSOt4bi4mI7tKJI6nN7HnsQOPTSMB5aUFfgMhhwxVf6DLgXTA/trained_model.tar 2024-08-29T10:49:08Z | INFO | [ Complete ] dest=/tmp/tmpgk_bdptw/weights size="172 MB" total_elapsed=1.521s url=https://replicate.delivery/yhqm/OSOt4bi4mI7tKJI6nN7HnsQOPTSMB5aUFfgMhhwxVf6DLgXTA/trained_model.tar Downloaded weights in 1.55s Loaded LoRAs in 10.01s 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, 3.76it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.73it/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, 3.67it/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, 3.65it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.66it/s] 61%|██████ | 17/28 [00:04<00:03, 3.66it/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, 3.66it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.65it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.65it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.65it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.65it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.65it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.65it/s] 100%|██████████| 28/28 [00:07<00:00, 3.65it/s] 100%|██████████| 28/28 [00:07<00:00, 3.68it/s]
Prediction
fofr/flux-myst:e308e02cIDtc43dpw6mdrm60chkq1t598a0rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- MYST portrait
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "MYST portrait", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "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-myst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-myst:e308e02c7228ea840e5f7ab57005ef57e655e9ef2bcbd3e0dbdb8123c41330ac", { input: { model: "dev", prompt: "MYST portrait", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", 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-myst using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-myst:e308e02c7228ea840e5f7ab57005ef57e655e9ef2bcbd3e0dbdb8123c41330ac", input={ "model": "dev", "prompt": "MYST portrait", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "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-myst 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": "e308e02c7228ea840e5f7ab57005ef57e655e9ef2bcbd3e0dbdb8123c41330ac", "input": { "model": "dev", "prompt": "MYST portrait", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "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": "2024-08-29T10:52:20.411938Z", "created_at": "2024-08-29T10:52:02.595000Z", "data_removed": false, "error": null, "id": "tc43dpw6mdrm60chkq1t598a0r", "input": { "model": "dev", "prompt": "MYST portrait", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 8758\nPrompt: MYST portrait\ntxt2img mode\nUsing dev model\nfree=9644439969792\nDownloading weights\n2024-08-29T10:52:02Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpvobjbe3n/weights url=https://replicate.delivery/yhqm/OSOt4bi4mI7tKJI6nN7HnsQOPTSMB5aUFfgMhhwxVf6DLgXTA/trained_model.tar\n2024-08-29T10:52:04Z | INFO | [ Complete ] dest=/tmp/tmpvobjbe3n/weights size=\"172 MB\" total_elapsed=1.394s url=https://replicate.delivery/yhqm/OSOt4bi4mI7tKJI6nN7HnsQOPTSMB5aUFfgMhhwxVf6DLgXTA/trained_model.tar\nDownloaded weights in 1.43s\nLoaded LoRAs in 9.77s\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, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.98it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/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, 3.75it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.70it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.70it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.71it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 17.808643036, "total_time": 17.816938 }, "output": [ "https://replicate.delivery/yhqm/34fKSqEeLCpjc0Zf5hL8SdVDEiA2V4e7E7KrOwpKHf9mcC8aC/out-0.webp" ], "started_at": "2024-08-29T10:52:02.603295Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tc43dpw6mdrm60chkq1t598a0r", "cancel": "https://api.replicate.com/v1/predictions/tc43dpw6mdrm60chkq1t598a0r/cancel" }, "version": "e308e02c7228ea840e5f7ab57005ef57e655e9ef2bcbd3e0dbdb8123c41330ac" }
Generated inUsing seed: 8758 Prompt: MYST portrait txt2img mode Using dev model free=9644439969792 Downloading weights 2024-08-29T10:52:02Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpvobjbe3n/weights url=https://replicate.delivery/yhqm/OSOt4bi4mI7tKJI6nN7HnsQOPTSMB5aUFfgMhhwxVf6DLgXTA/trained_model.tar 2024-08-29T10:52:04Z | INFO | [ Complete ] dest=/tmp/tmpvobjbe3n/weights size="172 MB" total_elapsed=1.394s url=https://replicate.delivery/yhqm/OSOt4bi4mI7tKJI6nN7HnsQOPTSMB5aUFfgMhhwxVf6DLgXTA/trained_model.tar Downloaded weights in 1.43s Loaded LoRAs in 9.77s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.69it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.98it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/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, 3.75it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.74it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.72it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.71it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.71it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.70it/s] 50%|█████ | 14/28 [00:03<00:03, 3.70it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.70it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.70it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.70it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.70it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.70it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.70it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.70it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.70it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.71it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]
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