vcollos / nanda
- Public
- 149 runs
-
H100
Prediction
vcollos/nanda:3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9cID28jwtc2gg9rm80cn8fgbchm0f4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- portrait of Nanda sitted on the chair with sexy face
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "portrait of Nanda sitted on the chair with sexy face", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport 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 vcollos/nanda using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "vcollos/nanda:3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9c", { input: { model: "dev", prompt: "portrait of Nanda sitted on the chair with sexy face", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, 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 replicateImport the client:import replicateRun vcollos/nanda using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "vcollos/nanda:3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9c", input={ "model": "dev", "prompt": "portrait of Nanda sitted on the chair with sexy face", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "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 vcollos/nanda 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": "vcollos/nanda:3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9c", "input": { "model": "dev", "prompt": "portrait of Nanda sitted on the chair with sexy face", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "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": "2025-02-26T20:09:37.680447Z", "created_at": "2025-02-26T20:08:49.026000Z", "data_removed": false, "error": null, "id": "28jwtc2gg9rm80cn8fgbchm0f4", "input": { "model": "dev", "prompt": "portrait of Nanda sitted on the chair with sexy face", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "free=29246543106048\nDownloading weights\n2025-02-26T20:09:26Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp6oz65bbr/weights url=https://replicate.delivery/xezq/pUuHgp0bblayDxNmLpTHBgdjekjtDOKRt2aOuKbTdlp3DpJKA/trained_model.tar\n2025-02-26T20:09:28Z | INFO | [ Complete ] dest=/tmp/tmp6oz65bbr/weights size=\"172 MB\" total_elapsed=1.959s url=https://replicate.delivery/xezq/pUuHgp0bblayDxNmLpTHBgdjekjtDOKRt2aOuKbTdlp3DpJKA/trained_model.tar\nDownloaded weights in 1.98s\nLoaded LoRAs in 4.46s\nUsing seed: 54049\nPrompt: portrait of Nanda sitted on the chair with sexy face\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:06, 4.06it/s]\n 7%|▋ | 2/28 [00:00<00:05, 4.58it/s]\n 11%|█ | 3/28 [00:00<00:05, 4.32it/s]\n 14%|█▍ | 4/28 [00:00<00:05, 4.20it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 4.13it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 4.10it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 4.08it/s]\n 29%|██▊ | 8/28 [00:01<00:04, 4.07it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 4.06it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 4.04it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 4.05it/s]\n 43%|████▎ | 12/28 [00:02<00:03, 4.04it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 4.04it/s]\n 50%|█████ | 14/28 [00:03<00:03, 4.03it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 4.03it/s]\n 57%|█████▋ | 16/28 [00:03<00:02, 4.03it/s]\n 61%|██████ | 17/28 [00:04<00:02, 4.03it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 4.03it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 4.04it/s]\n 71%|███████▏ | 20/28 [00:04<00:01, 4.03it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 4.04it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 4.04it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 4.03it/s]\n 86%|████████▌ | 24/28 [00:05<00:00, 4.03it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 4.03it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 4.03it/s]\n 96%|█████████▋| 27/28 [00:06<00:00, 4.04it/s]\n100%|██████████| 28/28 [00:06<00:00, 4.04it/s]\n100%|██████████| 28/28 [00:06<00:00, 4.06it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 11.62294927, "total_time": 48.654447 }, "output": [ "https://replicate.delivery/xezq/Mmf3gBCN2h0uLqMMBMNzKG90ZK6IpNGbYowouE7D09gAOpJKA/out-0.webp" ], "started_at": "2025-02-26T20:09:26.057497Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-sa3w4mkkqu7lhxqy67werxstg4wg73gzcgj7gpxkcjc5djejdz6a", "get": "https://api.replicate.com/v1/predictions/28jwtc2gg9rm80cn8fgbchm0f4", "cancel": "https://api.replicate.com/v1/predictions/28jwtc2gg9rm80cn8fgbchm0f4/cancel" }, "version": "3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9c" }Generated infree=29246543106048 Downloading weights 2025-02-26T20:09:26Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp6oz65bbr/weights url=https://replicate.delivery/xezq/pUuHgp0bblayDxNmLpTHBgdjekjtDOKRt2aOuKbTdlp3DpJKA/trained_model.tar 2025-02-26T20:09:28Z | INFO | [ Complete ] dest=/tmp/tmp6oz65bbr/weights size="172 MB" total_elapsed=1.959s url=https://replicate.delivery/xezq/pUuHgp0bblayDxNmLpTHBgdjekjtDOKRt2aOuKbTdlp3DpJKA/trained_model.tar Downloaded weights in 1.98s Loaded LoRAs in 4.46s Using seed: 54049 Prompt: portrait of Nanda sitted on the chair with sexy face [!] txt2img mode 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:06, 4.06it/s] 7%|▋ | 2/28 [00:00<00:05, 4.58it/s] 11%|█ | 3/28 [00:00<00:05, 4.32it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.20it/s] 18%|█▊ | 5/28 [00:01<00:05, 4.13it/s] 21%|██▏ | 6/28 [00:01<00:05, 4.10it/s] 25%|██▌ | 7/28 [00:01<00:05, 4.08it/s] 29%|██▊ | 8/28 [00:01<00:04, 4.07it/s] 32%|███▏ | 9/28 [00:02<00:04, 4.06it/s] 36%|███▌ | 10/28 [00:02<00:04, 4.04it/s] 39%|███▉ | 11/28 [00:02<00:04, 4.05it/s] 43%|████▎ | 12/28 [00:02<00:03, 4.04it/s] 46%|████▋ | 13/28 [00:03<00:03, 4.04it/s] 50%|█████ | 14/28 [00:03<00:03, 4.03it/s] 54%|█████▎ | 15/28 [00:03<00:03, 4.03it/s] 57%|█████▋ | 16/28 [00:03<00:02, 4.03it/s] 61%|██████ | 17/28 [00:04<00:02, 4.03it/s] 64%|██████▍ | 18/28 [00:04<00:02, 4.03it/s] 68%|██████▊ | 19/28 [00:04<00:02, 4.04it/s] 71%|███████▏ | 20/28 [00:04<00:01, 4.03it/s] 75%|███████▌ | 21/28 [00:05<00:01, 4.04it/s] 79%|███████▊ | 22/28 [00:05<00:01, 4.04it/s] 82%|████████▏ | 23/28 [00:05<00:01, 4.03it/s] 86%|████████▌ | 24/28 [00:05<00:00, 4.03it/s] 89%|████████▉ | 25/28 [00:06<00:00, 4.03it/s] 93%|█████████▎| 26/28 [00:06<00:00, 4.03it/s] 96%|█████████▋| 27/28 [00:06<00:00, 4.04it/s] 100%|██████████| 28/28 [00:06<00:00, 4.04it/s] 100%|██████████| 28/28 [00:06<00:00, 4.06it/s] Total safe images: 1 out of 1Prediction
vcollos/nanda:3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9cID6wxazb7rydrm80cn8gw8anrw70StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- image
- model
- dev
- prompt
- portrait of Nanda sitted on the chair with sexy face
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "image": "https://replicate.delivery/pbxt/MZJD8mBPEO56XqO0uhL4Tvq0pJdhoLxSabfUZYhjFIrsrBqa/u7644314267_The_photo_of_a_beautiful_38-year-old_woman_sittin_c9680efc-5b3b-42bb-84cb-307ae59f6654_3.png", "model": "dev", "prompt": "portrait of Nanda sitted on the chair with sexy face", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport 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 vcollos/nanda using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "vcollos/nanda:3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9c", { input: { image: "https://replicate.delivery/pbxt/MZJD8mBPEO56XqO0uhL4Tvq0pJdhoLxSabfUZYhjFIrsrBqa/u7644314267_The_photo_of_a_beautiful_38-year-old_woman_sittin_c9680efc-5b3b-42bb-84cb-307ae59f6654_3.png", model: "dev", prompt: "portrait of Nanda sitted on the chair with sexy face", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, 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 replicateImport the client:import replicateRun vcollos/nanda using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "vcollos/nanda:3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9c", input={ "image": "https://replicate.delivery/pbxt/MZJD8mBPEO56XqO0uhL4Tvq0pJdhoLxSabfUZYhjFIrsrBqa/u7644314267_The_photo_of_a_beautiful_38-year-old_woman_sittin_c9680efc-5b3b-42bb-84cb-307ae59f6654_3.png", "model": "dev", "prompt": "portrait of Nanda sitted on the chair with sexy face", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "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 vcollos/nanda 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": "vcollos/nanda:3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9c", "input": { "image": "https://replicate.delivery/pbxt/MZJD8mBPEO56XqO0uhL4Tvq0pJdhoLxSabfUZYhjFIrsrBqa/u7644314267_The_photo_of_a_beautiful_38-year-old_woman_sittin_c9680efc-5b3b-42bb-84cb-307ae59f6654_3.png", "model": "dev", "prompt": "portrait of Nanda sitted on the chair with sexy face", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "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": "2025-02-26T21:45:49.537016Z", "created_at": "2025-02-26T21:45:39.315000Z", "data_removed": false, "error": null, "id": "6wxazb7rydrm80cn8gw8anrw70", "input": { "image": "https://replicate.delivery/pbxt/MZJD8mBPEO56XqO0uhL4Tvq0pJdhoLxSabfUZYhjFIrsrBqa/u7644314267_The_photo_of_a_beautiful_38-year-old_woman_sittin_c9680efc-5b3b-42bb-84cb-307ae59f6654_3.png", "model": "dev", "prompt": "portrait of Nanda sitted on the chair with sexy face", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "free=28515503955968\nDownloading weights\n2025-02-26T21:45:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpt7j14y2c/weights url=https://replicate.delivery/xezq/pUuHgp0bblayDxNmLpTHBgdjekjtDOKRt2aOuKbTdlp3DpJKA/trained_model.tar\n2025-02-26T21:45:40Z | INFO | [ Complete ] dest=/tmp/tmpt7j14y2c/weights size=\"172 MB\" total_elapsed=1.341s url=https://replicate.delivery/xezq/pUuHgp0bblayDxNmLpTHBgdjekjtDOKRt2aOuKbTdlp3DpJKA/trained_model.tar\nDownloaded weights in 1.37s\nLoaded LoRAs in 1.95s\nUsing seed: 49088\nPrompt: portrait of Nanda sitted on the chair with sexy face\nInput image size: 928x1232\n[!] Resizing input image from 928x1232 to 928x1232\n[!] img2img mode\n 0%| | 0/23 [00:00<?, ?it/s]\n 4%|▍ | 1/23 [00:00<00:19, 1.11it/s]\n 9%|▊ | 2/23 [00:01<00:11, 1.89it/s]\n 13%|█▎ | 3/23 [00:01<00:08, 2.43it/s]\n 17%|█▋ | 4/23 [00:01<00:06, 2.80it/s]\n 22%|██▏ | 5/23 [00:01<00:05, 3.07it/s]\n 26%|██▌ | 6/23 [00:02<00:05, 3.26it/s]\n 30%|███ | 7/23 [00:02<00:04, 3.39it/s]\n 35%|███▍ | 8/23 [00:02<00:04, 3.48it/s]\n 39%|███▉ | 9/23 [00:03<00:03, 3.54it/s]\n 43%|████▎ | 10/23 [00:03<00:03, 3.59it/s]\n 48%|████▊ | 11/23 [00:03<00:03, 3.62it/s]\n 52%|█████▏ | 12/23 [00:03<00:03, 3.64it/s]\n 57%|█████▋ | 13/23 [00:04<00:02, 3.65it/s]\n 61%|██████ | 14/23 [00:04<00:02, 3.66it/s]\n 65%|██████▌ | 15/23 [00:04<00:02, 3.67it/s]\n 70%|██████▉ | 16/23 [00:04<00:01, 3.68it/s]\n 74%|███████▍ | 17/23 [00:05<00:01, 3.68it/s]\n 78%|███████▊ | 18/23 [00:05<00:01, 3.69it/s]\n 83%|████████▎ | 19/23 [00:05<00:01, 3.69it/s]\n 87%|████████▋ | 20/23 [00:06<00:00, 3.69it/s]\n 91%|█████████▏| 21/23 [00:06<00:00, 3.69it/s]\n 96%|█████████▌| 22/23 [00:06<00:00, 3.69it/s]\n100%|██████████| 23/23 [00:06<00:00, 3.69it/s]\n100%|██████████| 23/23 [00:06<00:00, 3.35it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 10.189778861, "total_time": 10.222016 }, "output": [ "https://replicate.delivery/xezq/fPome5v0RRvTmk6zMS1GfuqmxpDTydpMJEmDqXN30CuasnmoA/out-0.webp" ], "started_at": "2025-02-26T21:45:39.347237Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-oq4se2hwy2cb4k3zmoib3gqdfqvxrhurzaqcvwsglfobtahtw67q", "get": "https://api.replicate.com/v1/predictions/6wxazb7rydrm80cn8gw8anrw70", "cancel": "https://api.replicate.com/v1/predictions/6wxazb7rydrm80cn8gw8anrw70/cancel" }, "version": "3e5775f157cc1a171e88180468dcde811d007b68eddbef3db438cdd8dad8eb9c" }Generated infree=28515503955968 Downloading weights 2025-02-26T21:45:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpt7j14y2c/weights url=https://replicate.delivery/xezq/pUuHgp0bblayDxNmLpTHBgdjekjtDOKRt2aOuKbTdlp3DpJKA/trained_model.tar 2025-02-26T21:45:40Z | INFO | [ Complete ] dest=/tmp/tmpt7j14y2c/weights size="172 MB" total_elapsed=1.341s url=https://replicate.delivery/xezq/pUuHgp0bblayDxNmLpTHBgdjekjtDOKRt2aOuKbTdlp3DpJKA/trained_model.tar Downloaded weights in 1.37s Loaded LoRAs in 1.95s Using seed: 49088 Prompt: portrait of Nanda sitted on the chair with sexy face Input image size: 928x1232 [!] Resizing input image from 928x1232 to 928x1232 [!] img2img mode 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:19, 1.11it/s] 9%|▊ | 2/23 [00:01<00:11, 1.89it/s] 13%|█▎ | 3/23 [00:01<00:08, 2.43it/s] 17%|█▋ | 4/23 [00:01<00:06, 2.80it/s] 22%|██▏ | 5/23 [00:01<00:05, 3.07it/s] 26%|██▌ | 6/23 [00:02<00:05, 3.26it/s] 30%|███ | 7/23 [00:02<00:04, 3.39it/s] 35%|███▍ | 8/23 [00:02<00:04, 3.48it/s] 39%|███▉ | 9/23 [00:03<00:03, 3.54it/s] 43%|████▎ | 10/23 [00:03<00:03, 3.59it/s] 48%|████▊ | 11/23 [00:03<00:03, 3.62it/s] 52%|█████▏ | 12/23 [00:03<00:03, 3.64it/s] 57%|█████▋ | 13/23 [00:04<00:02, 3.65it/s] 61%|██████ | 14/23 [00:04<00:02, 3.66it/s] 65%|██████▌ | 15/23 [00:04<00:02, 3.67it/s] 70%|██████▉ | 16/23 [00:04<00:01, 3.68it/s] 74%|███████▍ | 17/23 [00:05<00:01, 3.68it/s] 78%|███████▊ | 18/23 [00:05<00:01, 3.69it/s] 83%|████████▎ | 19/23 [00:05<00:01, 3.69it/s] 87%|████████▋ | 20/23 [00:06<00:00, 3.69it/s] 91%|█████████▏| 21/23 [00:06<00:00, 3.69it/s] 96%|█████████▌| 22/23 [00:06<00:00, 3.69it/s] 100%|██████████| 23/23 [00:06<00:00, 3.69it/s] 100%|██████████| 23/23 [00:06<00:00, 3.35it/s] Total safe images: 1 out of 1
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