fofr
/
flux-mona-lisa
Flux lora, use the term "MNALSA" to trigger generation
- Public
- 3.4K runs
-
H100
Prediction
fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41Input
- model
- dev
- prompt
- a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp, award winning portrait photography
- lora_scale
- 0.9
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 2.5
- output_quality
- 95
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp, award winning portrait photography", "lora_scale": 0.9, "num_outputs": 1, "aspect_ratio": "1:1", "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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", { input: { model: "dev", prompt: "a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp, award winning portrait photography", lora_scale: 0.9, num_outputs: 1, aspect_ratio: "1:1", 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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", input={ "model": "dev", "prompt": "a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp, award winning portrait photography", "lora_scale": 0.9, "num_outputs": 1, "aspect_ratio": "1:1", "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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", "input": { "model": "dev", "prompt": "a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp, award winning portrait photography", "lora_scale": 0.9, "num_outputs": 1, "aspect_ratio": "1:1", "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": "2024-08-26T22:31:50.101293Z", "created_at": "2024-08-26T22:31:22.235000Z", "data_removed": false, "error": null, "id": "mhg55jdkfdrm40chj38b3ymnew", "input": { "model": "dev", "prompt": "a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp, award winning portrait photography", "lora_scale": 0.9, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 95, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 3606\nPrompt: a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp, award winning portrait photography\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 18.56s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.56it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.97it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.76it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.66it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.57it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.56it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.56it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.55it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.55it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.55it/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, 3.54it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.53it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.54it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.54it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.55it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.55it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.55it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.54it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.55it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.55it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.54it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.54it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.55it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.57it/s]", "metrics": { "predict_time": 26.992761135, "total_time": 27.866293 }, "output": [ "https://replicate.delivery/yhqm/OQPHQ9kRw9ZpIBMub19XY8NxKznMDA50eSEjpx52QP3qoVrJA/out-0.webp" ], "started_at": "2024-08-26T22:31:23.108532Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mhg55jdkfdrm40chj38b3ymnew", "cancel": "https://api.replicate.com/v1/predictions/mhg55jdkfdrm40chj38b3ymnew/cancel" }, "version": "6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41" }Generated inUsing seed: 3606 Prompt: a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp, award winning portrait photography txt2img mode Using dev model Loaded LoRAs in 18.56s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.56it/s] 7%|▋ | 2/28 [00:00<00:06, 3.97it/s] 11%|█ | 3/28 [00:00<00:06, 3.76it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.66it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.57it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.56it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.56it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.55it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.55it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.55it/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, 3.54it/s] 61%|██████ | 17/28 [00:04<00:03, 3.53it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.54it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.54it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.55it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.55it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.55it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.54it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.55it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.55it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.54it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.54it/s] 100%|██████████| 28/28 [00:07<00:00, 3.55it/s] 100%|██████████| 28/28 [00:07<00:00, 3.57it/s]Prediction
fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41Input
- model
- dev
- prompt
- a photo of MNALSA woman with pink hair at a rave
- lora_scale
- 0.9
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 2.5
- output_quality
- 95
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a photo of MNALSA woman with pink hair at a rave", "lora_scale": 0.9, "num_outputs": 1, "aspect_ratio": "1:1", "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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", { input: { model: "dev", prompt: "a photo of MNALSA woman with pink hair at a rave", lora_scale: 0.9, num_outputs: 1, aspect_ratio: "1:1", 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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", input={ "model": "dev", "prompt": "a photo of MNALSA woman with pink hair at a rave", "lora_scale": 0.9, "num_outputs": 1, "aspect_ratio": "1:1", "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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", "input": { "model": "dev", "prompt": "a photo of MNALSA woman with pink hair at a rave", "lora_scale": 0.9, "num_outputs": 1, "aspect_ratio": "1:1", "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": "2024-08-26T22:36:32.188481Z", "created_at": "2024-08-26T22:36:22.667000Z", "data_removed": false, "error": null, "id": "bzwnb9t91drm20chj3atbjk6jm", "input": { "model": "dev", "prompt": "a photo of MNALSA woman with pink hair at a rave", "lora_scale": 0.9, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 95, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 27728\nPrompt: a photo of MNALSA woman with pink hair at a rave\ntxt2img mode\nUsing dev model\nWeights already loaded\nLoaded LoRAs in 0.05s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.47it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.84it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.66it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.61it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.58it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.55it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.53it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.53it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.53it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.51it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.51it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.51it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.51it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.51it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.51it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.51it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.51it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.49it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.51it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.51it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.51it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.51it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.51it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.51it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.51it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.51it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.51it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.51it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.53it/s]", "metrics": { "predict_time": 8.548042144, "total_time": 9.521481 }, "output": [ "https://replicate.delivery/yhqm/apYK6kZFfZUYRyoJ11NzhHY2YXbrjCHajYIiN9EznGR4qVrJA/out-0.webp" ], "started_at": "2024-08-26T22:36:23.640439Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/bzwnb9t91drm20chj3atbjk6jm", "cancel": "https://api.replicate.com/v1/predictions/bzwnb9t91drm20chj3atbjk6jm/cancel" }, "version": "6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41" }Generated inUsing seed: 27728 Prompt: a photo of MNALSA woman with pink hair at a rave txt2img mode Using dev model Weights already loaded Loaded LoRAs in 0.05s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.47it/s] 7%|▋ | 2/28 [00:00<00:06, 3.84it/s] 11%|█ | 3/28 [00:00<00:06, 3.66it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.61it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.58it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.55it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.53it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.53it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.53it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.51it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.51it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.51it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.51it/s] 50%|█████ | 14/28 [00:03<00:03, 3.51it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.51it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.51it/s] 61%|██████ | 17/28 [00:04<00:03, 3.51it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.49it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.51it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.51it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.51it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.51it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.51it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.51it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.51it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.51it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.51it/s] 100%|██████████| 28/28 [00:07<00:00, 3.51it/s] 100%|██████████| 28/28 [00:07<00:00, 3.53it/s]Prediction
fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41IDwrnf0t8y6nrm40chj3gbdk8my4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a CNSTLL photo of MNALSA woman in beautiful twilight
- extra_lora
- adirik/flux-cinestill
- lora_scale
- 0.9
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 2.5
- output_quality
- 95
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a CNSTLL photo of MNALSA woman in beautiful twilight", "extra_lora": "adirik/flux-cinestill", "lora_scale": 0.9, "num_outputs": 4, "aspect_ratio": "1:1", "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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", { input: { model: "dev", prompt: "a CNSTLL photo of MNALSA woman in beautiful twilight", extra_lora: "adirik/flux-cinestill", lora_scale: 0.9, num_outputs: 4, aspect_ratio: "1:1", 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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", input={ "model": "dev", "prompt": "a CNSTLL photo of MNALSA woman in beautiful twilight", "extra_lora": "adirik/flux-cinestill", "lora_scale": 0.9, "num_outputs": 4, "aspect_ratio": "1:1", "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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", "input": { "model": "dev", "prompt": "a CNSTLL photo of MNALSA woman in beautiful twilight", "extra_lora": "adirik/flux-cinestill", "lora_scale": 0.9, "num_outputs": 4, "aspect_ratio": "1:1", "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": "2024-08-26T22:49:46.588229Z", "created_at": "2024-08-26T22:48:12.597000Z", "data_removed": false, "error": null, "id": "wrnf0t8y6nrm40chj3gbdk8my4", "input": { "model": "dev", "prompt": "a CNSTLL photo of MNALSA woman in beautiful twilight", "extra_lora": "adirik/flux-cinestill", "lora_scale": 0.9, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 95, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 17397\nPrompt: a CNSTLL photo of MNALSA woman in beautiful twilight\ntxt2img mode\nUsing dev model\nLoading extra LoRA weights from: adirik/flux-cinestill\nfree=9108634718208\nDownloading weights\n2024-08-26T22:48:31Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp8ka8ago5/weights url=https://replicate.com/adirik/flux-cinestill/_weights\n2024-08-26T22:48:31Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/3vhWyl3iACrCN9x53rEu7Lwit5hzZ9qDrKVi0wngSrNNheqJA/trained_model.tar url=https://replicate.com/adirik/flux-cinestill/_weights\n2024-08-26T22:48:34Z | INFO | [ Complete ] dest=/tmp/tmp8ka8ago5/weights size=\"172 MB\" total_elapsed=3.079s url=https://replicate.com/adirik/flux-cinestill/_weights\nDownloaded weights in 3.12s\nLoaded LoRAs in 59.63s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.14s/it]\n 7%|▋ | 2/28 [00:02<00:27, 1.04s/it]\n 11%|█ | 3/28 [00:03<00:27, 1.08s/it]\n 14%|█▍ | 4/28 [00:04<00:26, 1.11s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.12s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.12s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.13s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.13s/it]\n 32%|███▏ | 9/28 [00:10<00:21, 1.14s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.14s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.14s/it]\n 43%|████▎ | 12/28 [00:13<00:18, 1.14s/it]\n 46%|████▋ | 13/28 [00:14<00:17, 1.14s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.14s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.14s/it]\n 57%|█████▋ | 16/28 [00:18<00:13, 1.14s/it]\n 61%|██████ | 17/28 [00:19<00:12, 1.14s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.14s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.14s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.14s/it]\n 75%|███████▌ | 21/28 [00:23<00:08, 1.14s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.14s/it]\n 82%|████████▏ | 23/28 [00:26<00:05, 1.14s/it]\n 86%|████████▌ | 24/28 [00:27<00:04, 1.14s/it]\n 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.14s/it]", "metrics": { "predict_time": 93.178711565, "total_time": 93.991229 }, "output": [ "https://replicate.delivery/yhqm/ZGf9IC6w0Px4QCoCYRpjT3poBQwKD8GLifRvGxLRMrGKirWTA/out-0.webp", "https://replicate.delivery/yhqm/361vNNeAn3yqIiw4wj4NWmuiNLJO0bpQuUl54X3S1JaFxVrJA/out-1.webp", "https://replicate.delivery/yhqm/jbQwSH1bR6rPK5FOaC9q5INXStNdgT0jAxcL3gbp9oji4q1E/out-2.webp", "https://replicate.delivery/yhqm/1BPAJWm4kgpdKhO2kj9UWLkfmFwpvjSxnIT0ik2vZdVFxVrJA/out-3.webp" ], "started_at": "2024-08-26T22:48:13.409517Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/wrnf0t8y6nrm40chj3gbdk8my4", "cancel": "https://api.replicate.com/v1/predictions/wrnf0t8y6nrm40chj3gbdk8my4/cancel" }, "version": "6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41" }Generated inUsing seed: 17397 Prompt: a CNSTLL photo of MNALSA woman in beautiful twilight txt2img mode Using dev model Loading extra LoRA weights from: adirik/flux-cinestill free=9108634718208 Downloading weights 2024-08-26T22:48:31Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp8ka8ago5/weights url=https://replicate.com/adirik/flux-cinestill/_weights 2024-08-26T22:48:31Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/3vhWyl3iACrCN9x53rEu7Lwit5hzZ9qDrKVi0wngSrNNheqJA/trained_model.tar url=https://replicate.com/adirik/flux-cinestill/_weights 2024-08-26T22:48:34Z | INFO | [ Complete ] dest=/tmp/tmp8ka8ago5/weights size="172 MB" total_elapsed=3.079s url=https://replicate.com/adirik/flux-cinestill/_weights Downloaded weights in 3.12s Loaded LoRAs in 59.63s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.14s/it] 7%|▋ | 2/28 [00:02<00:27, 1.04s/it] 11%|█ | 3/28 [00:03<00:27, 1.08s/it] 14%|█▍ | 4/28 [00:04<00:26, 1.11s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.12s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.12s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.13s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.13s/it] 32%|███▏ | 9/28 [00:10<00:21, 1.14s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.14s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.14s/it] 43%|████▎ | 12/28 [00:13<00:18, 1.14s/it] 46%|████▋ | 13/28 [00:14<00:17, 1.14s/it] 50%|█████ | 14/28 [00:15<00:15, 1.14s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.14s/it] 57%|█████▋ | 16/28 [00:18<00:13, 1.14s/it] 61%|██████ | 17/28 [00:19<00:12, 1.14s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.14s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.14s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.14s/it] 75%|███████▌ | 21/28 [00:23<00:08, 1.14s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.14s/it] 82%|████████▏ | 23/28 [00:26<00:05, 1.14s/it] 86%|████████▌ | 24/28 [00:27<00:04, 1.14s/it] 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.14s/it]Prediction
fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41Input
- model
- dev
- prompt
- a CNSTLL photo of MNALSA woman in beautiful night time, long exposure, stars, her face is uplit, cityscape, perfect eyes
- extra_lora
- adirik/flux-cinestill
- lora_scale
- 0.9
- num_outputs
- 4
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 2.5
- output_quality
- 95
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a CNSTLL photo of MNALSA woman in beautiful night time, long exposure, stars, her face is uplit, cityscape, perfect eyes", "extra_lora": "adirik/flux-cinestill", "lora_scale": 0.9, "num_outputs": 4, "aspect_ratio": "16:9", "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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", { input: { model: "dev", prompt: "a CNSTLL photo of MNALSA woman in beautiful night time, long exposure, stars, her face is uplit, cityscape, perfect eyes", extra_lora: "adirik/flux-cinestill", lora_scale: 0.9, num_outputs: 4, aspect_ratio: "16:9", 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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", input={ "model": "dev", "prompt": "a CNSTLL photo of MNALSA woman in beautiful night time, long exposure, stars, her face is uplit, cityscape, perfect eyes", "extra_lora": "adirik/flux-cinestill", "lora_scale": 0.9, "num_outputs": 4, "aspect_ratio": "16:9", "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-mona-lisa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/flux-mona-lisa:6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41", "input": { "model": "dev", "prompt": "a CNSTLL photo of MNALSA woman in beautiful night time, long exposure, stars, her face is uplit, cityscape, perfect eyes", "extra_lora": "adirik/flux-cinestill", "lora_scale": 0.9, "num_outputs": 4, "aspect_ratio": "16:9", "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": "2024-08-26T22:58:08.829511Z", "created_at": "2024-08-26T22:57:01.301000Z", "data_removed": false, "error": null, "id": "6566xhsfenrm00chj3m90hpt7c", "input": { "model": "dev", "prompt": "a CNSTLL photo of MNALSA woman in beautiful night time, long exposure, stars, her face is uplit, cityscape, perfect eyes", "extra_lora": "adirik/flux-cinestill", "lora_scale": 0.9, "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 2.5, "output_quality": 95, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 9283\nPrompt: a CNSTLL photo of MNALSA woman in beautiful night time, long exposure, stars, her face is uplit, cityscape, perfect eyes\ntxt2img mode\nUsing dev model\nLoading extra LoRA weights from: adirik/flux-cinestill\nfree=9592084684800\nDownloading weights\n2024-08-26T22:57:21Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpwlg7lkcp/weights url=https://replicate.com/adirik/flux-cinestill/_weights\n2024-08-26T22:57:21Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/3vhWyl3iACrCN9x53rEu7Lwit5hzZ9qDrKVi0wngSrNNheqJA/trained_model.tar url=https://replicate.com/adirik/flux-cinestill/_weights\n2024-08-26T22:57:24Z | INFO | [ Complete ] dest=/tmp/tmpwlg7lkcp/weights size=\"172 MB\" total_elapsed=3.228s url=https://replicate.com/adirik/flux-cinestill/_weights\nDownloaded weights in 3.26s\nLoaded LoRAs in 33.59s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:26, 1.02s/it]\n 11%|█ | 3/28 [00:03<00:26, 1.07s/it]\n 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it]\n 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:28<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 67.00430051, "total_time": 67.528511 }, "output": [ "https://replicate.delivery/yhqm/Njufu9H42dSYQitboHELMaGFhTqJuCoULX2j1k3qepUAqrWTA/out-0.webp", "https://replicate.delivery/yhqm/pb1oBbY6uxrCKZ5FGJknDE63UF3LHFnwqVGSfKgyoSGA1VrJA/out-1.webp", "https://replicate.delivery/yhqm/DJbHaRA1Qu7KM9C9BiJlQjOJ3y49cjXNGgjvtNBGf1MA1VrJA/out-2.webp", "https://replicate.delivery/yhqm/eeLjBEWsbpiXbUX6iZHH6wfhokf7DfSSrYcQHDVKY8tBQd1aC/out-3.webp" ], "started_at": "2024-08-26T22:57:01.825210Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/6566xhsfenrm00chj3m90hpt7c", "cancel": "https://api.replicate.com/v1/predictions/6566xhsfenrm00chj3m90hpt7c/cancel" }, "version": "6e7e34b8d739ab9d4d9a468ef773b5cd85a5c36b11f885379061ba2c70219d41" }Generated inUsing seed: 9283 Prompt: a CNSTLL photo of MNALSA woman in beautiful night time, long exposure, stars, her face is uplit, cityscape, perfect eyes txt2img mode Using dev model Loading extra LoRA weights from: adirik/flux-cinestill free=9592084684800 Downloading weights 2024-08-26T22:57:21Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpwlg7lkcp/weights url=https://replicate.com/adirik/flux-cinestill/_weights 2024-08-26T22:57:21Z | INFO | [ Redirect ] redirect_url=https://replicate.delivery/yhqm/3vhWyl3iACrCN9x53rEu7Lwit5hzZ9qDrKVi0wngSrNNheqJA/trained_model.tar url=https://replicate.com/adirik/flux-cinestill/_weights 2024-08-26T22:57:24Z | INFO | [ Complete ] dest=/tmp/tmpwlg7lkcp/weights size="172 MB" total_elapsed=3.228s url=https://replicate.com/adirik/flux-cinestill/_weights Downloaded weights in 3.26s Loaded LoRAs in 33.59s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:26, 1.02s/it] 11%|█ | 3/28 [00:03<00:26, 1.07s/it] 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it] 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:18<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:28<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]
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