fofr
/
flux-mjv3
Flux lora trained on Midjourney v3 outputs from 2022, use "a dream, in the style of MJV3" to trigger generation, also try increasing lora strength above 1
- Public
- 3.9K runs
-
H100
- Paper
Prediction
fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2IDw5t4g358xhrm20chk3hrdp7ntcStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a dream, art in the style of MJV3
- 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": "a dream, art in the style of MJV3", "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 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", { input: { model: "dev", prompt: "a dream, art in the style of MJV3", 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 } } ); // 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-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", input={ "model": "dev", "prompt": "a dream, art in the style of MJV3", "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.
Run fofr/flux-mjv3 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": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3", "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/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T12:09:35.163454Z", "created_at": "2024-08-28T12:09:02.444000Z", "data_removed": false, "error": null, "id": "w5t4g358xhrm20chk3hrdp7ntc", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3", "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: 27711\nPrompt: a dream, art in the style of MJV3\ntxt2img mode\nUsing dev model\nfree=9723924205568\nDownloading weights\n2024-08-28T12:09:10Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp_5gm4268/weights url=https://replicate.delivery/yhqm/LXtvmmckSo5cKpre0tvW5n1gcryh5Wl7dO8sg48GuTtLKmrJA/trained_model.tar\n2024-08-28T12:09:13Z | INFO | [ Complete ] dest=/tmp/tmp_5gm4268/weights size=\"344 MB\" total_elapsed=3.243s url=https://replicate.delivery/yhqm/LXtvmmckSo5cKpre0tvW5n1gcryh5Wl7dO8sg48GuTtLKmrJA/trained_model.tar\nDownloaded weights in 3.29s\nLoaded LoRAs in 16.96s\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, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/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, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/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, 3.67it/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, 3.66it/s]\n 61%|██████ | 17/28 [00:04<00:02, 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, 3.66it/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": 25.0931602, "total_time": 32.719454 }, "output": [ "https://replicate.delivery/yhqm/FvlBroEZLsq0CZFrJ93fg8xLTSeZ4TLhzpwMJSmZyo5frYumA/out-0.webp" ], "started_at": "2024-08-28T12:09:10.070294Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/w5t4g358xhrm20chk3hrdp7ntc", "cancel": "https://api.replicate.com/v1/predictions/w5t4g358xhrm20chk3hrdp7ntc/cancel" }, "version": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2" }Generated inUsing seed: 27711 Prompt: a dream, art in the style of MJV3 txt2img mode Using dev model free=9723924205568 Downloading weights 2024-08-28T12:09:10Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp_5gm4268/weights url=https://replicate.delivery/yhqm/LXtvmmckSo5cKpre0tvW5n1gcryh5Wl7dO8sg48GuTtLKmrJA/trained_model.tar 2024-08-28T12:09:13Z | INFO | [ Complete ] dest=/tmp/tmp_5gm4268/weights size="344 MB" total_elapsed=3.243s url=https://replicate.delivery/yhqm/LXtvmmckSo5cKpre0tvW5n1gcryh5Wl7dO8sg48GuTtLKmrJA/trained_model.tar Downloaded weights in 3.29s Loaded LoRAs in 16.96s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.96it/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, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/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, 3.67it/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, 3.66it/s] 61%|██████ | 17/28 [00:04<00:02, 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, 3.66it/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-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2ID7eay751afhrm00chk3t9ab50gmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a dream, art in the style of MJV3, a photo of a living room interior, misty, abstract, weird, double exposure with a ghostly figure
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 3:2
- output_format
- webp
- guidance_scale
- 2.5
- output_quality
- 95
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a dream, art in the style of MJV3, a photo of a living room interior, misty, abstract, weird, double exposure with a ghostly figure", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 95, "extra_lora_scale": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", { input: { model: "dev", prompt: "a dream, art in the style of MJV3, a photo of a living room interior, misty, abstract, weird, double exposure with a ghostly figure", lora_scale: 1, num_outputs: 4, aspect_ratio: "3:2", output_format: "webp", guidance_scale: 2.5, output_quality: 95, extra_lora_scale: 0.8, 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-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", input={ "model": "dev", "prompt": "a dream, art in the style of MJV3, a photo of a living room interior, misty, abstract, weird, double exposure with a ghostly figure", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 95, "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.
Run fofr/flux-mjv3 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": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3, a photo of a living room interior, misty, abstract, weird, double exposure with a ghostly figure", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 95, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T12:27:44.448830Z", "created_at": "2024-08-28T12:27:04.188000Z", "data_removed": false, "error": null, "id": "7eay751afhrm00chk3t9ab50gm", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3, a photo of a living room interior, misty, abstract, weird, double exposure with a ghostly figure", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 95, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 5527\nPrompt: a dream, art in the style of MJV3, a photo of a living room interior, misty, abstract, weird, double exposure with a ghostly figure\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 11.48s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:26, 1.03it/s]\n 7%|▋ | 2/28 [00:01<00:22, 1.18it/s]\n 11%|█ | 3/28 [00:02<00:22, 1.11it/s]\n 14%|█▍ | 4/28 [00:03<00:22, 1.08it/s]\n 18%|█▊ | 5/28 [00:04<00:21, 1.06it/s]\n 21%|██▏ | 6/28 [00:05<00:20, 1.05it/s]\n 25%|██▌ | 7/28 [00:06<00:20, 1.04it/s]\n 29%|██▊ | 8/28 [00:07<00:19, 1.04it/s]\n 32%|███▏ | 9/28 [00:08<00:18, 1.04it/s]\n 36%|███▌ | 10/28 [00:09<00:17, 1.03it/s]\n 39%|███▉ | 11/28 [00:10<00:16, 1.03it/s]\n 43%|████▎ | 12/28 [00:11<00:15, 1.03it/s]\n 46%|████▋ | 13/28 [00:12<00:14, 1.03it/s]\n 50%|█████ | 14/28 [00:13<00:13, 1.03it/s]\n 54%|█████▎ | 15/28 [00:14<00:12, 1.03it/s]\n 57%|█████▋ | 16/28 [00:15<00:11, 1.03it/s]\n 61%|██████ | 17/28 [00:16<00:10, 1.03it/s]\n 64%|██████▍ | 18/28 [00:17<00:09, 1.03it/s]\n 68%|██████▊ | 19/28 [00:18<00:08, 1.03it/s]\n 71%|███████▏ | 20/28 [00:19<00:07, 1.03it/s]\n 75%|███████▌ | 21/28 [00:20<00:06, 1.03it/s]\n 79%|███████▊ | 22/28 [00:21<00:05, 1.03it/s]\n 82%|████████▏ | 23/28 [00:22<00:04, 1.03it/s]\n 86%|████████▌ | 24/28 [00:23<00:03, 1.03it/s]\n 89%|████████▉ | 25/28 [00:24<00:02, 1.03it/s]\n 93%|█████████▎| 26/28 [00:25<00:01, 1.03it/s]\n 96%|█████████▋| 27/28 [00:26<00:00, 1.03it/s]\n100%|██████████| 28/28 [00:27<00:00, 1.03it/s]\n100%|██████████| 28/28 [00:27<00:00, 1.04it/s]", "metrics": { "predict_time": 40.251826113, "total_time": 40.26083 }, "output": [ "https://replicate.delivery/yhqm/0jhgnAahT5IBOdRBA58SYUkaABldGZE1MLxhOSD4NwAwJz1E/out-0.webp", "https://replicate.delivery/yhqm/atPCMfLuOfmhUkI0VhGIj5ZhnorO7T2ycdC1ANUn9TuAnMXTA/out-1.webp", "https://replicate.delivery/yhqm/5uOHKd41IjrVItXbE7dcBXs5xrUrfTMBQvfqbIt0aApAnMXTA/out-2.webp", "https://replicate.delivery/yhqm/W5KcegeucpgFEUblN33evYlI2Zxxdlun615IxW5GTDmAOZumA/out-3.webp" ], "started_at": "2024-08-28T12:27:04.197004Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7eay751afhrm00chk3t9ab50gm", "cancel": "https://api.replicate.com/v1/predictions/7eay751afhrm00chk3t9ab50gm/cancel" }, "version": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2" }Generated inUsing seed: 5527 Prompt: a dream, art in the style of MJV3, a photo of a living room interior, misty, abstract, weird, double exposure with a ghostly figure txt2img mode Using dev model Loaded LoRAs in 11.48s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:26, 1.03it/s] 7%|▋ | 2/28 [00:01<00:22, 1.18it/s] 11%|█ | 3/28 [00:02<00:22, 1.11it/s] 14%|█▍ | 4/28 [00:03<00:22, 1.08it/s] 18%|█▊ | 5/28 [00:04<00:21, 1.06it/s] 21%|██▏ | 6/28 [00:05<00:20, 1.05it/s] 25%|██▌ | 7/28 [00:06<00:20, 1.04it/s] 29%|██▊ | 8/28 [00:07<00:19, 1.04it/s] 32%|███▏ | 9/28 [00:08<00:18, 1.04it/s] 36%|███▌ | 10/28 [00:09<00:17, 1.03it/s] 39%|███▉ | 11/28 [00:10<00:16, 1.03it/s] 43%|████▎ | 12/28 [00:11<00:15, 1.03it/s] 46%|████▋ | 13/28 [00:12<00:14, 1.03it/s] 50%|█████ | 14/28 [00:13<00:13, 1.03it/s] 54%|█████▎ | 15/28 [00:14<00:12, 1.03it/s] 57%|█████▋ | 16/28 [00:15<00:11, 1.03it/s] 61%|██████ | 17/28 [00:16<00:10, 1.03it/s] 64%|██████▍ | 18/28 [00:17<00:09, 1.03it/s] 68%|██████▊ | 19/28 [00:18<00:08, 1.03it/s] 71%|███████▏ | 20/28 [00:19<00:07, 1.03it/s] 75%|███████▌ | 21/28 [00:20<00:06, 1.03it/s] 79%|███████▊ | 22/28 [00:21<00:05, 1.03it/s] 82%|████████▏ | 23/28 [00:22<00:04, 1.03it/s] 86%|████████▌ | 24/28 [00:23<00:03, 1.03it/s] 89%|████████▉ | 25/28 [00:24<00:02, 1.03it/s] 93%|█████████▎| 26/28 [00:25<00:01, 1.03it/s] 96%|█████████▋| 27/28 [00:26<00:00, 1.03it/s] 100%|██████████| 28/28 [00:27<00:00, 1.03it/s] 100%|██████████| 28/28 [00:27<00:00, 1.04it/s]Prediction
fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2IDzpy0pkzfe9rm20chk3v8fh9zvgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a dream, art in the style of MJV3, a woman
- 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": "a dream, art in the style of MJV3, a woman", "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 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", { input: { model: "dev", prompt: "a dream, art in the style of MJV3, a woman", 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 } } ); // 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-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", input={ "model": "dev", "prompt": "a dream, art in the style of MJV3, a woman", "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.
Run fofr/flux-mjv3 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": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3, a woman", "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/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T12:30:39.087380Z", "created_at": "2024-08-28T12:30:05.682000Z", "data_removed": false, "error": null, "id": "zpy0pkzfe9rm20chk3v8fh9zvg", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3, a woman", "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: 9730\nPrompt: a dream, art in the style of MJV3, a woman\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 25.29s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.71it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.27it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.99it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.77it/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, 3.73it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.72it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.71it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.71it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/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, 3.70it/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, 3.70it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.73it/s]", "metrics": { "predict_time": 33.392772774, "total_time": 33.40538 }, "output": [ "https://replicate.delivery/yhqm/WmxXwrnQ0sZeByV0FuWmhoC8tZtVHsbSFkldVL0fFXlupMXTA/out-0.webp" ], "started_at": "2024-08-28T12:30:05.694607Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zpy0pkzfe9rm20chk3v8fh9zvg", "cancel": "https://api.replicate.com/v1/predictions/zpy0pkzfe9rm20chk3v8fh9zvg/cancel" }, "version": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2" }Generated inUsing seed: 9730 Prompt: a dream, art in the style of MJV3, a woman txt2img mode Using dev model Loaded LoRAs in 25.29s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.71it/s] 7%|▋ | 2/28 [00:00<00:06, 4.27it/s] 11%|█ | 3/28 [00:00<00:06, 3.99it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.87it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.81it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.77it/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, 3.73it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.72it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.72it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.71it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.71it/s] 50%|█████ | 14/28 [00:03<00:03, 3.71it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.71it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.71it/s] 61%|██████ | 17/28 [00:04<00:02, 3.71it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.70it/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, 3.70it/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, 3.70it/s] 100%|██████████| 28/28 [00:07<00:00, 3.73it/s]Prediction
fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2IDjgnezw4my1rm20chk408xk2j0gStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a dream, art in the style of MJV3, a face with dripping makeup
- 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": "a dream, art in the style of MJV3, a face with dripping makeup", "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 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", { input: { model: "dev", prompt: "a dream, art in the style of MJV3, a face with dripping makeup", 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 } } ); // 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-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", input={ "model": "dev", "prompt": "a dream, art in the style of MJV3, a face with dripping makeup", "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.
Run fofr/flux-mjv3 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": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3, a face with dripping makeup", "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/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T12:41:08.607949Z", "created_at": "2024-08-28T12:40:37.872000Z", "data_removed": false, "error": null, "id": "jgnezw4my1rm20chk408xk2j0g", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3, a face with dripping makeup", "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: 20295\nPrompt: a dream, art in the style of MJV3, a face with dripping makeup\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 11.18s\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, 4.23it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/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, 3.68it/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, 3.68it/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, 3.67it/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, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]", "metrics": { "predict_time": 19.274699016, "total_time": 30.735949 }, "output": [ "https://replicate.delivery/yhqm/P9J11pU27x4bDlxwPh4UfAlSnlRdfSlb0WZxMMd8djAkzMXTA/out-0.webp" ], "started_at": "2024-08-28T12:40:49.333250Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jgnezw4my1rm20chk408xk2j0g", "cancel": "https://api.replicate.com/v1/predictions/jgnezw4my1rm20chk408xk2j0g/cancel" }, "version": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2" }Generated inUsing seed: 20295 Prompt: a dream, art in the style of MJV3, a face with dripping makeup txt2img mode Using dev model Loaded LoRAs in 11.18s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.67it/s] 7%|▋ | 2/28 [00:00<00:06, 4.23it/s] 11%|█ | 3/28 [00:00<00:06, 3.96it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/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, 3.68it/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, 3.68it/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, 3.67it/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, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s]Prediction
fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2IDjfsz91n9j1rm60chk43tmddt90StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a dream, art in the style of MJV3, a photo of a face
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 2.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a dream, art in the style of MJV3, a photo of a face", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", { input: { model: "dev", prompt: "a dream, art in the style of MJV3, a photo of a face", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 2.5, output_quality: 80, extra_lora_scale: 0.8, 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-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", input={ "model": "dev", "prompt": "a dream, art in the style of MJV3, a photo of a face", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "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.
Run fofr/flux-mjv3 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": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3, a photo of a face", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T12:48:42.356828Z", "created_at": "2024-08-28T12:48:21.904000Z", "data_removed": false, "error": null, "id": "jfsz91n9j1rm60chk43tmddt90", "input": { "model": "dev", "prompt": "a dream, art in the style of MJV3, a photo of a face", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 26949\nPrompt: a dream, art in the style of MJV3, a photo of a face\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 12.31s\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, 4.23it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.96it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.78it/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, 3.71it/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, 3.68it/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, 3.68it/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, 3.68it/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": 20.439904463, "total_time": 20.452828 }, "output": [ "https://replicate.delivery/yhqm/QnelOKB2LywbeEmVHCgfLJ45qV88ajD0AHRPob8Ip06U1ZumA/out-0.webp" ], "started_at": "2024-08-28T12:48:21.916924Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jfsz91n9j1rm60chk43tmddt90", "cancel": "https://api.replicate.com/v1/predictions/jfsz91n9j1rm60chk43tmddt90/cancel" }, "version": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2" }Generated inUsing seed: 26949 Prompt: a dream, art in the style of MJV3, a photo of a face txt2img mode Using dev model Loaded LoRAs in 12.31s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.68it/s] 7%|▋ | 2/28 [00:00<00:06, 4.23it/s] 11%|█ | 3/28 [00:00<00:06, 3.96it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.84it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.78it/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, 3.71it/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, 3.68it/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, 3.68it/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, 3.68it/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-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2IDtwhzxgjdr5rm60chk46s1cnhkmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- the word "v3" in cursive in the style of MJV3, against a beautiful flowery forest
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 2.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "the word \"v3\" in cursive in the style of MJV3, against a beautiful flowery forest", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/flux-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", { input: { model: "dev", prompt: "the word \"v3\" in cursive in the style of MJV3, against a beautiful flowery forest", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 2.5, output_quality: 80, extra_lora_scale: 0.8, 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-mjv3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mjv3:f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", input={ "model": "dev", "prompt": "the word \"v3\" in cursive in the style of MJV3, against a beautiful flowery forest", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "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.
Run fofr/flux-mjv3 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": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2", "input": { "model": "dev", "prompt": "the word \\"v3\\" in cursive in the style of MJV3, against a beautiful flowery forest", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T12:54:52.309581Z", "created_at": "2024-08-28T12:54:31.617000Z", "data_removed": false, "error": null, "id": "twhzxgjdr5rm60chk46s1cnhkm", "input": { "model": "dev", "prompt": "the word \"v3\" in cursive in the style of MJV3, against a beautiful flowery forest", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 40215\nPrompt: the word \"v3\" in cursive in the style of MJV3, against a beautiful flowery forest\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 12.52s\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, 3.78it/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, 3.70it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.69it/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, 3.68it/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, 3.67it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.70it/s]", "metrics": { "predict_time": 20.684510711, "total_time": 20.692581 }, "output": [ "https://replicate.delivery/yhqm/wXowvnO9im7DNtY3znNxRc4nPqC6gFbqzS62RoHQXHNHQz1E/out-0.webp" ], "started_at": "2024-08-28T12:54:31.625071Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/twhzxgjdr5rm60chk46s1cnhkm", "cancel": "https://api.replicate.com/v1/predictions/twhzxgjdr5rm60chk46s1cnhkm/cancel" }, "version": "f8bba190713142471df7ef2adba00fe9c84f5d63b5c48702082f2718e7f4d8b2" }Generated inUsing seed: 40215 Prompt: the word "v3" in cursive in the style of MJV3, against a beautiful flowery forest txt2img mode Using dev model Loaded LoRAs in 12.52s 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, 3.78it/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, 3.70it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.69it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.69it/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, 3.68it/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, 3.67it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.67it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.67it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.67it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.67it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.70it/s]
Want to make some of these yourself?
Run this model