phxdev1 / flux-ska-band
Bowler hats, checkered suits and brass horns. It was the 90s people! Or, it could be any band I guess, I dunno, I'm not your dad.
- Public
- 21 runs
-
H100
- Weights
Prediction
phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01IDkqw9qawcjxrj00cj7ptvx7f0qcStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- model
- schnell
- prompt
- "Tackleshaft", A ska band playing in a garage, saxophone, trombone
- extra_lora
- adirik/flux-cinestill
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 2
- output_quality
- 100
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "schnell", "prompt": "\"Tackleshaft\", A ska band playing in a garage, saxophone, trombone", "extra_lora": "adirik/flux-cinestill", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import 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 phxdev1/flux-ska-band using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01", { input: { model: "schnell", prompt: "\"Tackleshaft\", A ska band playing in a garage, saxophone, trombone", extra_lora: "adirik/flux-cinestill", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 2, output_quality: 100, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run phxdev1/flux-ska-band using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01", input={ "model": "schnell", "prompt": "\"Tackleshaft\", A ska band playing in a garage, saxophone, trombone", "extra_lora": "adirik/flux-cinestill", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run phxdev1/flux-ska-band 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": "phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01", "input": { "model": "schnell", "prompt": "\\"Tackleshaft\\", A ska band playing in a garage, saxophone, trombone", "extra_lora": "adirik/flux-cinestill", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "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": "2024-09-29T12:16:24.095429Z", "created_at": "2024-09-29T12:16:01.175000Z", "data_removed": false, "error": null, "id": "kqw9qawcjxrj00cj7ptvx7f0qc", "input": { "model": "schnell", "prompt": "\"Tackleshaft\", A ska band playing in a garage, saxophone, trombone", "extra_lora": "adirik/flux-cinestill", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 16771\nPrompt: \"Tackleshaft\", A ska band playing in a garage, saxophone, trombone\n[!] txt2img mode\nUsing schnell model\nLoading extra LoRA weights from: adirik/flux-cinestill\nfree=3039268913152\nDownloading weights\n2024-09-29T12:16:01Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpd9zlaooj/weights url=https://replicate.delivery/yhqm/1SeFnDtk7fkfJphAkFZfPFiEUxVEVffFRiXx7JNDfsfvv0uhTA/trained_model.tar\n2024-09-29T12:16:02Z | INFO | [ Complete ] dest=/tmp/tmpd9zlaooj/weights size=\"172 MB\" total_elapsed=1.031s url=https://replicate.delivery/yhqm/1SeFnDtk7fkfJphAkFZfPFiEUxVEVffFRiXx7JNDfsfvv0uhTA/trained_model.tar\nDownloaded weights in 1.06s\nLoaded LoRAs in 2.70s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:18, 1.43it/s]\n 7%|▋ | 2/28 [00:01<00:16, 1.57it/s]\n 11%|█ | 3/28 [00:01<00:16, 1.50it/s]\n 14%|█▍ | 4/28 [00:02<00:16, 1.47it/s]\n 18%|█▊ | 5/28 [00:03<00:15, 1.46it/s]\n 21%|██▏ | 6/28 [00:04<00:15, 1.45it/s]\n 25%|██▌ | 7/28 [00:04<00:14, 1.44it/s]\n 29%|██▊ | 8/28 [00:05<00:13, 1.44it/s]\n 32%|███▏ | 9/28 [00:06<00:13, 1.44it/s]\n 36%|███▌ | 10/28 [00:06<00:12, 1.44it/s]\n 39%|███▉ | 11/28 [00:07<00:11, 1.43it/s]\n 43%|████▎ | 12/28 [00:08<00:11, 1.43it/s]\n 46%|████▋ | 13/28 [00:08<00:10, 1.43it/s]\n 50%|█████ | 14/28 [00:09<00:09, 1.43it/s]\n 54%|█████▎ | 15/28 [00:10<00:09, 1.43it/s]\n 57%|█████▋ | 16/28 [00:11<00:08, 1.43it/s]\n 61%|██████ | 17/28 [00:11<00:07, 1.43it/s]\n 64%|██████▍ | 18/28 [00:12<00:06, 1.43it/s]\n 68%|██████▊ | 19/28 [00:13<00:06, 1.43it/s]\n 71%|███████▏ | 20/28 [00:13<00:05, 1.43it/s]\n 75%|███████▌ | 21/28 [00:14<00:04, 1.43it/s]\n 79%|███████▊ | 22/28 [00:15<00:04, 1.43it/s]\n 82%|████████▏ | 23/28 [00:15<00:03, 1.43it/s]\n 86%|████████▌ | 24/28 [00:16<00:02, 1.43it/s]\n 89%|████████▉ | 25/28 [00:17<00:02, 1.43it/s]\n 93%|█████████▎| 26/28 [00:18<00:01, 1.43it/s]\n 96%|█████████▋| 27/28 [00:18<00:00, 1.43it/s]\n100%|██████████| 28/28 [00:19<00:00, 1.43it/s]\n100%|██████████| 28/28 [00:19<00:00, 1.44it/s]", "metrics": { "predict_time": 22.909475254, "total_time": 22.920429 }, "output": [ "https://replicate.delivery/yhqm/yEZvveb3yoWRCqd1qfW092Cl1emThHTpEGfIgkCKzHQfi7NcC/out-0.webp" ], "started_at": "2024-09-29T12:16:01.185954Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/kqw9qawcjxrj00cj7ptvx7f0qc", "cancel": "https://api.replicate.com/v1/predictions/kqw9qawcjxrj00cj7ptvx7f0qc/cancel" }, "version": "dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01" }
Generated inUsing seed: 16771 Prompt: "Tackleshaft", A ska band playing in a garage, saxophone, trombone [!] txt2img mode Using schnell model Loading extra LoRA weights from: adirik/flux-cinestill free=3039268913152 Downloading weights 2024-09-29T12:16:01Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpd9zlaooj/weights url=https://replicate.delivery/yhqm/1SeFnDtk7fkfJphAkFZfPFiEUxVEVffFRiXx7JNDfsfvv0uhTA/trained_model.tar 2024-09-29T12:16:02Z | INFO | [ Complete ] dest=/tmp/tmpd9zlaooj/weights size="172 MB" total_elapsed=1.031s url=https://replicate.delivery/yhqm/1SeFnDtk7fkfJphAkFZfPFiEUxVEVffFRiXx7JNDfsfvv0uhTA/trained_model.tar Downloaded weights in 1.06s Loaded LoRAs in 2.70s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:18, 1.43it/s] 7%|▋ | 2/28 [00:01<00:16, 1.57it/s] 11%|█ | 3/28 [00:01<00:16, 1.50it/s] 14%|█▍ | 4/28 [00:02<00:16, 1.47it/s] 18%|█▊ | 5/28 [00:03<00:15, 1.46it/s] 21%|██▏ | 6/28 [00:04<00:15, 1.45it/s] 25%|██▌ | 7/28 [00:04<00:14, 1.44it/s] 29%|██▊ | 8/28 [00:05<00:13, 1.44it/s] 32%|███▏ | 9/28 [00:06<00:13, 1.44it/s] 36%|███▌ | 10/28 [00:06<00:12, 1.44it/s] 39%|███▉ | 11/28 [00:07<00:11, 1.43it/s] 43%|████▎ | 12/28 [00:08<00:11, 1.43it/s] 46%|████▋ | 13/28 [00:08<00:10, 1.43it/s] 50%|█████ | 14/28 [00:09<00:09, 1.43it/s] 54%|█████▎ | 15/28 [00:10<00:09, 1.43it/s] 57%|█████▋ | 16/28 [00:11<00:08, 1.43it/s] 61%|██████ | 17/28 [00:11<00:07, 1.43it/s] 64%|██████▍ | 18/28 [00:12<00:06, 1.43it/s] 68%|██████▊ | 19/28 [00:13<00:06, 1.43it/s] 71%|███████▏ | 20/28 [00:13<00:05, 1.43it/s] 75%|███████▌ | 21/28 [00:14<00:04, 1.43it/s] 79%|███████▊ | 22/28 [00:15<00:04, 1.43it/s] 82%|████████▏ | 23/28 [00:15<00:03, 1.43it/s] 86%|████████▌ | 24/28 [00:16<00:02, 1.43it/s] 89%|████████▉ | 25/28 [00:17<00:02, 1.43it/s] 93%|█████████▎| 26/28 [00:18<00:01, 1.43it/s] 96%|█████████▋| 27/28 [00:18<00:00, 1.43it/s] 100%|██████████| 28/28 [00:19<00:00, 1.43it/s] 100%|██████████| 28/28 [00:19<00:00, 1.44it/s]
Prediction
phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01IDpt5wmpb57xrj40cj7pvaazraywStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- model
- schnell
- prompt
- "Tackleshaft", A ska band playing in a garage, saxophone, trombone
- extra_lora
- adirik/flux-cinestill
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 2
- output_quality
- 100
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "schnell", "prompt": "\"Tackleshaft\", A ska band playing in a garage, saxophone, trombone", "extra_lora": "adirik/flux-cinestill", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import 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 phxdev1/flux-ska-band using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01", { input: { model: "schnell", prompt: "\"Tackleshaft\", A ska band playing in a garage, saxophone, trombone", extra_lora: "adirik/flux-cinestill", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 2, output_quality: 100, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run phxdev1/flux-ska-band using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01", input={ "model": "schnell", "prompt": "\"Tackleshaft\", A ska band playing in a garage, saxophone, trombone", "extra_lora": "adirik/flux-cinestill", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run phxdev1/flux-ska-band 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": "phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01", "input": { "model": "schnell", "prompt": "\\"Tackleshaft\\", A ska band playing in a garage, saxophone, trombone", "extra_lora": "adirik/flux-cinestill", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "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": "2024-09-29T12:17:20.963652Z", "created_at": "2024-09-29T12:16:56.639000Z", "data_removed": false, "error": null, "id": "pt5wmpb57xrj40cj7pvaazrayw", "input": { "model": "schnell", "prompt": "\"Tackleshaft\", A ska band playing in a garage, saxophone, trombone", "extra_lora": "adirik/flux-cinestill", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 47540\nPrompt: \"Tackleshaft\", A ska band playing in a garage, saxophone, trombone\n[!] txt2img mode\nUsing schnell model\nLoading extra LoRA weights from: adirik/flux-cinestill\nfree=4735897755648\nDownloading weights\n2024-09-29T12:16:56Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmphxs21q9l/weights url=https://replicate.delivery/yhqm/1SeFnDtk7fkfJphAkFZfPFiEUxVEVffFRiXx7JNDfsfvv0uhTA/trained_model.tar\n2024-09-29T12:16:57Z | INFO | [ Complete ] dest=/tmp/tmphxs21q9l/weights size=\"172 MB\" total_elapsed=1.013s url=https://replicate.delivery/yhqm/1SeFnDtk7fkfJphAkFZfPFiEUxVEVffFRiXx7JNDfsfvv0uhTA/trained_model.tar\nDownloaded weights in 1.04s\nfree=4735725080576\nDownloading weights\n2024-09-29T12:16:58Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmps5qhgx92/weights url=https://replicate.com/adirik/flux-cinestill/_weights\n2024-09-29T12:16:58Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/3vhWyl3iACrCN9x53rEu7Lwit5hzZ9qDrKVi0wngSrNNheqJA/trained_model.tar url=https://replicate.com/adirik/flux-cinestill/_weights\n2024-09-29T12:16:59Z | INFO | [ Complete ] dest=/tmp/tmps5qhgx92/weights size=\"172 MB\" total_elapsed=1.323s url=https://replicate.com/adirik/flux-cinestill/_weights\nDownloaded weights in 1.35s\nLoaded LoRAs in 4.05s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:18, 1.43it/s]\n 7%|▋ | 2/28 [00:01<00:16, 1.57it/s]\n 11%|█ | 3/28 [00:01<00:16, 1.50it/s]\n 14%|█▍ | 4/28 [00:02<00:16, 1.48it/s]\n 18%|█▊ | 5/28 [00:03<00:15, 1.46it/s]\n 21%|██▏ | 6/28 [00:04<00:15, 1.45it/s]\n 25%|██▌ | 7/28 [00:04<00:14, 1.44it/s]\n 29%|██▊ | 8/28 [00:05<00:13, 1.44it/s]\n 32%|███▏ | 9/28 [00:06<00:13, 1.44it/s]\n 36%|███▌ | 10/28 [00:06<00:12, 1.44it/s]\n 39%|███▉ | 11/28 [00:07<00:11, 1.44it/s]\n 43%|████▎ | 12/28 [00:08<00:11, 1.44it/s]\n 46%|████▋ | 13/28 [00:08<00:10, 1.43it/s]\n 50%|█████ | 14/28 [00:09<00:09, 1.43it/s]\n 54%|█████▎ | 15/28 [00:10<00:09, 1.43it/s]\n 57%|█████▋ | 16/28 [00:11<00:08, 1.43it/s]\n 61%|██████ | 17/28 [00:11<00:07, 1.43it/s]\n 64%|██████▍ | 18/28 [00:12<00:06, 1.43it/s]\n 68%|██████▊ | 19/28 [00:13<00:06, 1.43it/s]\n 71%|███████▏ | 20/28 [00:13<00:05, 1.43it/s]\n 75%|███████▌ | 21/28 [00:14<00:04, 1.43it/s]\n 79%|███████▊ | 22/28 [00:15<00:04, 1.43it/s]\n 82%|████████▏ | 23/28 [00:15<00:03, 1.43it/s]\n 86%|████████▌ | 24/28 [00:16<00:02, 1.43it/s]\n 89%|████████▉ | 25/28 [00:17<00:02, 1.43it/s]\n 93%|█████████▎| 26/28 [00:18<00:01, 1.43it/s]\n 96%|█████████▋| 27/28 [00:18<00:00, 1.43it/s]\n100%|██████████| 28/28 [00:19<00:00, 1.43it/s]\n100%|██████████| 28/28 [00:19<00:00, 1.44it/s]", "metrics": { "predict_time": 24.315012755, "total_time": 24.324652 }, "output": [ "https://replicate.delivery/yhqm/uJ97FsB9OpI8KNipuawmcSTYfiO9JNEU5oP6q9gz0pLou3wJA/out-0.webp" ], "started_at": "2024-09-29T12:16:56.648639Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/pt5wmpb57xrj40cj7pvaazrayw", "cancel": "https://api.replicate.com/v1/predictions/pt5wmpb57xrj40cj7pvaazrayw/cancel" }, "version": "dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01" }
Generated inUsing seed: 47540 Prompt: "Tackleshaft", A ska band playing in a garage, saxophone, trombone [!] txt2img mode Using schnell model Loading extra LoRA weights from: adirik/flux-cinestill free=4735897755648 Downloading weights 2024-09-29T12:16:56Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmphxs21q9l/weights url=https://replicate.delivery/yhqm/1SeFnDtk7fkfJphAkFZfPFiEUxVEVffFRiXx7JNDfsfvv0uhTA/trained_model.tar 2024-09-29T12:16:57Z | INFO | [ Complete ] dest=/tmp/tmphxs21q9l/weights size="172 MB" total_elapsed=1.013s url=https://replicate.delivery/yhqm/1SeFnDtk7fkfJphAkFZfPFiEUxVEVffFRiXx7JNDfsfvv0uhTA/trained_model.tar Downloaded weights in 1.04s free=4735725080576 Downloading weights 2024-09-29T12:16:58Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmps5qhgx92/weights url=https://replicate.com/adirik/flux-cinestill/_weights 2024-09-29T12:16:58Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/3vhWyl3iACrCN9x53rEu7Lwit5hzZ9qDrKVi0wngSrNNheqJA/trained_model.tar url=https://replicate.com/adirik/flux-cinestill/_weights 2024-09-29T12:16:59Z | INFO | [ Complete ] dest=/tmp/tmps5qhgx92/weights size="172 MB" total_elapsed=1.323s url=https://replicate.com/adirik/flux-cinestill/_weights Downloaded weights in 1.35s Loaded LoRAs in 4.05s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:18, 1.43it/s] 7%|▋ | 2/28 [00:01<00:16, 1.57it/s] 11%|█ | 3/28 [00:01<00:16, 1.50it/s] 14%|█▍ | 4/28 [00:02<00:16, 1.48it/s] 18%|█▊ | 5/28 [00:03<00:15, 1.46it/s] 21%|██▏ | 6/28 [00:04<00:15, 1.45it/s] 25%|██▌ | 7/28 [00:04<00:14, 1.44it/s] 29%|██▊ | 8/28 [00:05<00:13, 1.44it/s] 32%|███▏ | 9/28 [00:06<00:13, 1.44it/s] 36%|███▌ | 10/28 [00:06<00:12, 1.44it/s] 39%|███▉ | 11/28 [00:07<00:11, 1.44it/s] 43%|████▎ | 12/28 [00:08<00:11, 1.44it/s] 46%|████▋ | 13/28 [00:08<00:10, 1.43it/s] 50%|█████ | 14/28 [00:09<00:09, 1.43it/s] 54%|█████▎ | 15/28 [00:10<00:09, 1.43it/s] 57%|█████▋ | 16/28 [00:11<00:08, 1.43it/s] 61%|██████ | 17/28 [00:11<00:07, 1.43it/s] 64%|██████▍ | 18/28 [00:12<00:06, 1.43it/s] 68%|██████▊ | 19/28 [00:13<00:06, 1.43it/s] 71%|███████▏ | 20/28 [00:13<00:05, 1.43it/s] 75%|███████▌ | 21/28 [00:14<00:04, 1.43it/s] 79%|███████▊ | 22/28 [00:15<00:04, 1.43it/s] 82%|████████▏ | 23/28 [00:15<00:03, 1.43it/s] 86%|████████▌ | 24/28 [00:16<00:02, 1.43it/s] 89%|████████▉ | 25/28 [00:17<00:02, 1.43it/s] 93%|█████████▎| 26/28 [00:18<00:01, 1.43it/s] 96%|█████████▋| 27/28 [00:18<00:00, 1.43it/s] 100%|██████████| 28/28 [00:19<00:00, 1.43it/s] 100%|██████████| 28/28 [00:19<00:00, 1.44it/s]
Prediction
phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01IDjfbk3a1zdsrj20cj7pxay6j6acStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- model
- schnell
- prompt
- A ska band, concert, through the crowd, no text
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 2
- output_quality
- 100
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 16
{ "model": "schnell", "prompt": "A ska band, concert, through the crowd, no text", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 16 }
Install Replicate’s Node.js client library:npm install replicate
Import 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 phxdev1/flux-ska-band using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01", { input: { model: "schnell", prompt: "A ska band, concert, through the crowd, no text", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 2, output_quality: 100, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 16 } } ); // 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 replicate
Import the client:import replicate
Run phxdev1/flux-ska-band using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01", input={ "model": "schnell", "prompt": "A ska band, concert, through the crowd, no text", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 16 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run phxdev1/flux-ska-band 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": "phxdev1/flux-ska-band:dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01", "input": { "model": "schnell", "prompt": "A ska band, concert, through the crowd, no text", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 16 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-29T12:21:19.709503Z", "created_at": "2024-09-29T12:21:09.102000Z", "data_removed": false, "error": null, "id": "jfbk3a1zdsrj20cj7pxay6j6ac", "input": { "model": "schnell", "prompt": "A ska band, concert, through the crowd, no text", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 16 }, "logs": "Using seed: 16656\nPrompt: A ska band, concert, through the crowd, no text\n[!] txt2img mode\nUsing schnell model\nWeights already loaded\nLoaded LoRAs in 0.04s\n 0%| | 0/16 [00:00<?, ?it/s]\n 6%|▋ | 1/16 [00:00<00:09, 1.61it/s]\n 12%|█▎ | 2/16 [00:01<00:07, 1.82it/s]\n 19%|█▉ | 3/16 [00:01<00:07, 1.72it/s]\n 25%|██▌ | 4/16 [00:02<00:07, 1.67it/s]\n 31%|███▏ | 5/16 [00:02<00:06, 1.65it/s]\n 38%|███▊ | 6/16 [00:03<00:06, 1.64it/s]\n 44%|████▍ | 7/16 [00:04<00:05, 1.63it/s]\n 50%|█████ | 8/16 [00:04<00:04, 1.63it/s]\n 56%|█████▋ | 9/16 [00:05<00:04, 1.62it/s]\n 62%|██████▎ | 10/16 [00:06<00:03, 1.62it/s]\n 69%|██████▉ | 11/16 [00:06<00:03, 1.62it/s]\n 75%|███████▌ | 12/16 [00:07<00:02, 1.62it/s]\n 81%|████████▏ | 13/16 [00:07<00:01, 1.61it/s]\n 88%|████████▊ | 14/16 [00:08<00:01, 1.61it/s]\n 94%|█████████▍| 15/16 [00:09<00:00, 1.61it/s]\n100%|██████████| 16/16 [00:09<00:00, 1.61it/s]\n100%|██████████| 16/16 [00:09<00:00, 1.63it/s]", "metrics": { "predict_time": 10.597446225, "total_time": 10.607503 }, "output": [ "https://replicate.delivery/yhqm/V1NFA8pwa8qXKl3yf8ee4hqZfOmhegP3ySLoRCjbeFu4P4b4E/out-0.webp" ], "started_at": "2024-09-29T12:21:09.112057Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jfbk3a1zdsrj20cj7pxay6j6ac", "cancel": "https://api.replicate.com/v1/predictions/jfbk3a1zdsrj20cj7pxay6j6ac/cancel" }, "version": "dd0ceb3ada21e0495d6532e0f771612b55c7227728cff01964a98e077de96f01" }
Generated inUsing seed: 16656 Prompt: A ska band, concert, through the crowd, no text [!] txt2img mode Using schnell model Weights already loaded Loaded LoRAs in 0.04s 0%| | 0/16 [00:00<?, ?it/s] 6%|▋ | 1/16 [00:00<00:09, 1.61it/s] 12%|█▎ | 2/16 [00:01<00:07, 1.82it/s] 19%|█▉ | 3/16 [00:01<00:07, 1.72it/s] 25%|██▌ | 4/16 [00:02<00:07, 1.67it/s] 31%|███▏ | 5/16 [00:02<00:06, 1.65it/s] 38%|███▊ | 6/16 [00:03<00:06, 1.64it/s] 44%|████▍ | 7/16 [00:04<00:05, 1.63it/s] 50%|█████ | 8/16 [00:04<00:04, 1.63it/s] 56%|█████▋ | 9/16 [00:05<00:04, 1.62it/s] 62%|██████▎ | 10/16 [00:06<00:03, 1.62it/s] 69%|██████▉ | 11/16 [00:06<00:03, 1.62it/s] 75%|███████▌ | 12/16 [00:07<00:02, 1.62it/s] 81%|████████▏ | 13/16 [00:07<00:01, 1.61it/s] 88%|████████▊ | 14/16 [00:08<00:01, 1.61it/s] 94%|█████████▍| 15/16 [00:09<00:00, 1.61it/s] 100%|██████████| 16/16 [00:09<00:00, 1.61it/s] 100%|██████████| 16/16 [00:09<00:00, 1.63it/s]
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