gajendrajha09
/
fluxloramimi
- Public
- 89 runs
-
H100
Prediction
gajendrajha09/fluxloramimi:4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0IDk4ebz170pnrm60chk50bh0y8dcStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Close up portrait of mimi as Basketball star
- 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": "Close up portrait of mimi as Basketball star", "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 gajendrajha09/fluxloramimi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "gajendrajha09/fluxloramimi:4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0", { input: { model: "dev", prompt: "Close up portrait of mimi as Basketball star", 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 gajendrajha09/fluxloramimi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "gajendrajha09/fluxloramimi:4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0", input={ "model": "dev", "prompt": "Close up portrait of mimi as Basketball star", "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 gajendrajha09/fluxloramimi 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": "4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0", "input": { "model": "dev", "prompt": "Close up portrait of mimi as Basketball star", "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": "2024-08-28T13:51:22.434432Z", "created_at": "2024-08-28T13:50:51.573000Z", "data_removed": false, "error": null, "id": "k4ebz170pnrm60chk50bh0y8dc", "input": { "model": "dev", "prompt": "Close up portrait of mimi as Basketball star", "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: 13650\nPrompt: Close up portrait of mimi as Basketball star\ntxt2img mode\nUsing dev model\nfree=9298407907328\nDownloading weights\n2024-08-28T13:51:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp2363lfi6/weights url=https://replicate.delivery/yhqm/91FVD6gsByq2Npwy7gjpcWrzcrT2cHeOO0gpWjZFKNVummrJA/trained_model.tar\n2024-08-28T13:51:06Z | INFO | [ Complete ] dest=/tmp/tmp2363lfi6/weights size=\"172 MB\" total_elapsed=1.446s url=https://replicate.delivery/yhqm/91FVD6gsByq2Npwy7gjpcWrzcrT2cHeOO0gpWjZFKNVummrJA/trained_model.tar\nDownloaded weights in 1.48s\nLoaded LoRAs in 9.78s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.66it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.21it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.94it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.82it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.76it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.72it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.70it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.66it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.66it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.65it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.65it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.65it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.65it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.65it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.65it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.65it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.65it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.65it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.65it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.65it/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, 3.68it/s]", "metrics": { "predict_time": 17.948838377, "total_time": 30.861432 }, "output": [ "https://replicate.delivery/yhqm/PrfF2iUgDRU9PSRNEv1D9bsDxJ6eD0U7KmAsog7Zi3wa1NXTA/out-0.webp" ], "started_at": "2024-08-28T13:51:04.485594Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/k4ebz170pnrm60chk50bh0y8dc", "cancel": "https://api.replicate.com/v1/predictions/k4ebz170pnrm60chk50bh0y8dc/cancel" }, "version": "4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0" }Generated inUsing seed: 13650 Prompt: Close up portrait of mimi as Basketball star txt2img mode Using dev model free=9298407907328 Downloading weights 2024-08-28T13:51:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp2363lfi6/weights url=https://replicate.delivery/yhqm/91FVD6gsByq2Npwy7gjpcWrzcrT2cHeOO0gpWjZFKNVummrJA/trained_model.tar 2024-08-28T13:51:06Z | INFO | [ Complete ] dest=/tmp/tmp2363lfi6/weights size="172 MB" total_elapsed=1.446s url=https://replicate.delivery/yhqm/91FVD6gsByq2Npwy7gjpcWrzcrT2cHeOO0gpWjZFKNVummrJA/trained_model.tar Downloaded weights in 1.48s Loaded LoRAs in 9.78s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.66it/s] 7%|▋ | 2/28 [00:00<00:06, 4.21it/s] 11%|█ | 3/28 [00:00<00:06, 3.94it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.82it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.76it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.72it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.70it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.69it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.68it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.67it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.66it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.66it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.66it/s] 50%|█████ | 14/28 [00:03<00:03, 3.65it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.65it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.65it/s] 61%|██████ | 17/28 [00:04<00:03, 3.65it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.65it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.65it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.65it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.65it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.65it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.65it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.66it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.66it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.65it/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, 3.68it/s]Prediction
gajendrajha09/fluxloramimi:4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0IDp2j23fpwt5rm00chk5gszk75d0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Mimi as spider girl, slim and young
- 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": "Mimi as spider girl, slim and young", "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 gajendrajha09/fluxloramimi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "gajendrajha09/fluxloramimi:4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0", { input: { model: "dev", prompt: "Mimi as spider girl, slim and young", 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 gajendrajha09/fluxloramimi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "gajendrajha09/fluxloramimi:4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0", input={ "model": "dev", "prompt": "Mimi as spider girl, slim and young", "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 gajendrajha09/fluxloramimi 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": "4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0", "input": { "model": "dev", "prompt": "Mimi as spider girl, slim and young", "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": "2024-08-28T14:27:22.965161Z", "created_at": "2024-08-28T14:26:53.265000Z", "data_removed": false, "error": null, "id": "p2j23fpwt5rm00chk5gszk75d0", "input": { "model": "dev", "prompt": "Mimi as spider girl, slim and young", "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: 60147\nPrompt: Mimi as spider girl, slim and young\ntxt2img mode\nUsing dev model\nfree=9388947189760\nDownloading weights\n2024-08-28T14:26:58Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpmoxx9ee3/weights url=https://replicate.delivery/yhqm/91FVD6gsByq2Npwy7gjpcWrzcrT2cHeOO0gpWjZFKNVummrJA/trained_model.tar\n2024-08-28T14:27:00Z | INFO | [ Complete ] dest=/tmp/tmpmoxx9ee3/weights size=\"172 MB\" total_elapsed=1.304s url=https://replicate.delivery/yhqm/91FVD6gsByq2Npwy7gjpcWrzcrT2cHeOO0gpWjZFKNVummrJA/trained_model.tar\nDownloaded weights in 1.33s\nLoaded LoRAs in 16.04s\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, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.95it/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, 3.74it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.69it/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, 3.67it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.67it/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": 24.165767908, "total_time": 29.700161 }, "output": [ "https://replicate.delivery/yhqm/nJPTtYu3T05wG5vMSeKJGcCjZfAHRJZ8WvnGTNOiuUaKXOXTA/out-0.webp" ], "started_at": "2024-08-28T14:26:58.799393Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/p2j23fpwt5rm00chk5gszk75d0", "cancel": "https://api.replicate.com/v1/predictions/p2j23fpwt5rm00chk5gszk75d0/cancel" }, "version": "4408c824cf6ec26def76a8f2c9e65d1935687db18a6ceab55386c42555de08b0" }Generated inUsing seed: 60147 Prompt: Mimi as spider girl, slim and young txt2img mode Using dev model free=9388947189760 Downloading weights 2024-08-28T14:26:58Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpmoxx9ee3/weights url=https://replicate.delivery/yhqm/91FVD6gsByq2Npwy7gjpcWrzcrT2cHeOO0gpWjZFKNVummrJA/trained_model.tar 2024-08-28T14:27:00Z | INFO | [ Complete ] dest=/tmp/tmpmoxx9ee3/weights size="172 MB" total_elapsed=1.304s url=https://replicate.delivery/yhqm/91FVD6gsByq2Npwy7gjpcWrzcrT2cHeOO0gpWjZFKNVummrJA/trained_model.tar Downloaded weights in 1.33s Loaded LoRAs in 16.04s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.68it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 3.95it/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, 3.74it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.71it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.69it/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, 3.67it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.67it/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]
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