enkey08
/
ganpatibappa
Ganpati image generation model trained on all Ganapati in Pune, India
- Public
- 73 runs
-
H100
Prediction
enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41IDd027vd8bn9rm60chjd4vas92xmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Bappa making presentations to a crowd of mice. The backdrop is a conference room, echoing modern, clean design. His eyes, focused, possibly asking the mice to get ready
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Bappa making presentations to a crowd of mice. The backdrop is a conference room, echoing modern, clean design. His eyes, focused, possibly asking the mice to get ready", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 enkey08/ganpatibappa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", { input: { model: "dev", prompt: "Bappa making presentations to a crowd of mice. The backdrop is a conference room, echoing modern, clean design. His eyes, focused, possibly asking the mice to get ready", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", 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 enkey08/ganpatibappa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", input={ "model": "dev", "prompt": "Bappa making presentations to a crowd of mice. The backdrop is a conference room, echoing modern, clean design. His eyes, focused, possibly asking the mice to get ready", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 enkey08/ganpatibappa 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": "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", "input": { "model": "dev", "prompt": "Bappa making presentations to a crowd of mice. The backdrop is a conference room, echoing modern, clean design. His eyes, focused, possibly asking the mice to get ready", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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": "2024-08-27T10:02:26.177264Z", "created_at": "2024-08-27T10:02:03.562000Z", "data_removed": false, "error": null, "id": "d027vd8bn9rm60chjd4vas92xm", "input": { "model": "dev", "prompt": "Bappa making presentations to a crowd of mice. The backdrop is a conference room, echoing modern, clean design. His eyes, focused, possibly asking the mice to get ready", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 65335\nPrompt: Bappa making presentations to a crowd of mice. The backdrop is a conference room, echoing modern, clean design. His eyes, focused, possibly asking the mice to get ready\ntxt2img mode\nUsing dev model\nfree=9222668537856\nDownloading weights\n2024-08-27T10:02:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpgdkanx1r/weights url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar\n2024-08-27T10:02:08Z | INFO | [ Complete ] dest=/tmp/tmpgdkanx1r/weights size=\"172 MB\" total_elapsed=3.720s url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar\nDownloaded weights in 3.76s\nLoaded LoRAs in 13.60s\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, 4.22it/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, 3.76it/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, 3.69it/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, 3.67it/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, 3.66it/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<00:03, 3.66it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.66it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/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, 3.67it/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, 3.67it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.66it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]", "metrics": { "predict_time": 21.654982119, "total_time": 22.615264 }, "output": [ "https://replicate.delivery/yhqm/6iOhnPliG5YqO98sHC8Lmu4dPfBDka3UGxwNbqbu5TBZsarJA/out-0.jpg" ], "started_at": "2024-08-27T10:02:04.522282Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/d027vd8bn9rm60chjd4vas92xm", "cancel": "https://api.replicate.com/v1/predictions/d027vd8bn9rm60chjd4vas92xm/cancel" }, "version": "99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41" }Generated inUsing seed: 65335 Prompt: Bappa making presentations to a crowd of mice. The backdrop is a conference room, echoing modern, clean design. His eyes, focused, possibly asking the mice to get ready txt2img mode Using dev model free=9222668537856 Downloading weights 2024-08-27T10:02:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpgdkanx1r/weights url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar 2024-08-27T10:02:08Z | INFO | [ Complete ] dest=/tmp/tmpgdkanx1r/weights size="172 MB" total_elapsed=3.720s url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar Downloaded weights in 3.76s Loaded LoRAs in 13.60s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.66it/s] 7%|▋ | 2/28 [00:00<00:06, 4.22it/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, 3.76it/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, 3.69it/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, 3.67it/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, 3.66it/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<00:03, 3.66it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.66it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.67it/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, 3.67it/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, 3.67it/s] 100%|██████████| 28/28 [00:07<00:00, 3.66it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s]Prediction
enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41ID1vs2rk5365rm60chjadv5s55gmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- create a cinematic photo of dagdushet halwai ganpati sitting and flying on an Indian eagle showering flowers on the city of Pune which visible from the top with it's archetectural heritage of Shaniwar wada and Saras bagh
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "create a cinematic photo of dagdushet halwai ganpati sitting and flying on an Indian eagle showering flowers on the city of Pune which visible from the top with it's archetectural heritage of Shaniwar wada and Saras bagh", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "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 enkey08/ganpatibappa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", { input: { model: "dev", prompt: "create a cinematic photo of dagdushet halwai ganpati sitting and flying on an Indian eagle showering flowers on the city of Pune which visible from the top with it's archetectural heritage of Shaniwar wada and Saras bagh", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", 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 enkey08/ganpatibappa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", input={ "model": "dev", "prompt": "create a cinematic photo of dagdushet halwai ganpati sitting and flying on an Indian eagle showering flowers on the city of Pune which visible from the top with it's archetectural heritage of Shaniwar wada and Saras bagh", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "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 enkey08/ganpatibappa 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": "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", "input": { "model": "dev", "prompt": "create a cinematic photo of dagdushet halwai ganpati sitting and flying on an Indian eagle showering flowers on the city of Pune which visible from the top with it\'s archetectural heritage of Shaniwar wada and Saras bagh", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "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": "2024-08-27T06:53:03.516176Z", "created_at": "2024-08-27T06:52:39.089000Z", "data_removed": false, "error": null, "id": "1vs2rk5365rm60chjadv5s55gm", "input": { "model": "dev", "prompt": "create a cinematic photo of dagdushet halwai ganpati sitting and flying on an Indian eagle showering flowers on the city of Pune which visible from the top with it's archetectural heritage of Shaniwar wada and Saras bagh", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 10735\nPrompt: create a cinematic photo of dagdushet halwai ganpati sitting and flying on an Indian eagle showering flowers on the city of Pune which visible from the top with it's archetectural heritage of Shaniwar wada and Saras bagh\ntxt2img mode\nUsing dev model\nfree=9749353181184\nDownloading weights\n2024-08-27T06:52:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpo63zyoc2/weights url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar\n2024-08-27T06:52:41Z | INFO | [ Complete ] dest=/tmp/tmpo63zyoc2/weights size=\"172 MB\" total_elapsed=1.607s url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar\nDownloaded weights in 1.65s\nLoaded LoRAs in 15.73s\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, 4.25it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.80it/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, 3.73it/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, 3.71it/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, 3.70it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.70it/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, 3.71it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/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": 23.79522044, "total_time": 24.427176 }, "output": [ "https://replicate.delivery/yhqm/Koz6xcjfuXVgX6fN8dMiyP8dWJfr9Ieg6C57Tc7ekeW1zps1E/out-0.webp" ], "started_at": "2024-08-27T06:52:39.720955Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/1vs2rk5365rm60chjadv5s55gm", "cancel": "https://api.replicate.com/v1/predictions/1vs2rk5365rm60chjadv5s55gm/cancel" }, "version": "99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41" }Generated inUsing seed: 10735 Prompt: create a cinematic photo of dagdushet halwai ganpati sitting and flying on an Indian eagle showering flowers on the city of Pune which visible from the top with it's archetectural heritage of Shaniwar wada and Saras bagh txt2img mode Using dev model free=9749353181184 Downloading weights 2024-08-27T06:52:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpo63zyoc2/weights url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar 2024-08-27T06:52:41Z | INFO | [ Complete ] dest=/tmp/tmpo63zyoc2/weights size="172 MB" total_elapsed=1.607s url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar Downloaded weights in 1.65s Loaded LoRAs in 15.73s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.68it/s] 7%|▋ | 2/28 [00:00<00:06, 4.25it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.80it/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, 3.73it/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, 3.71it/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, 3.70it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.70it/s] 61%|██████ | 17/28 [00:04<00:02, 3.70it/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, 3.71it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.71it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.70it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.71it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.71it/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
enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41ID694ds4fz9srm00chjcmtnk7954StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- silhouette of bappa
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "silhouette of bappa", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 enkey08/ganpatibappa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", { input: { model: "dev", prompt: "silhouette of bappa", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", 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 enkey08/ganpatibappa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", input={ "model": "dev", "prompt": "silhouette of bappa", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 enkey08/ganpatibappa 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": "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", "input": { "model": "dev", "prompt": "silhouette of bappa", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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": "2024-08-27T09:28:47.057951Z", "created_at": "2024-08-27T09:28:08.782000Z", "data_removed": false, "error": null, "id": "694ds4fz9srm00chjcmtnk7954", "input": { "model": "dev", "prompt": "silhouette of bappa", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 63144\nPrompt: silhouette of bappa\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 9.12s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.70it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.97it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.70it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.69it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.69it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.69it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.69it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.69it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.69it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.72it/s]", "metrics": { "predict_time": 17.097457508, "total_time": 38.275951 }, "output": [ "https://replicate.delivery/yhqm/Bzm2xHAtsd5lL9ri4KsMZD3jmpzIooAn6oTFtFvJ6OkTOt1E/out-0.jpg" ], "started_at": "2024-08-27T09:28:29.960493Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/694ds4fz9srm00chjcmtnk7954", "cancel": "https://api.replicate.com/v1/predictions/694ds4fz9srm00chjcmtnk7954/cancel" }, "version": "99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41" }Generated inUsing seed: 63144 Prompt: silhouette of bappa txt2img mode Using dev model Loaded LoRAs in 9.12s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.70it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 3.97it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.86it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.80it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.76it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.74it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.72it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.70it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.70it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.70it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.69it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.69it/s] 50%|█████ | 14/28 [00:03<00:03, 3.69it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.69it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.69it/s] 61%|██████ | 17/28 [00:04<00:02, 3.69it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.69it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.69it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.69it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.69it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.69it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.69it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.69it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.69it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.69it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.69it/s] 100%|██████████| 28/28 [00:07<00:00, 3.72it/s]Prediction
enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41IDdr8kth2yjdrm60chnkka46vmhrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Bappa playing cricket . Backdrop is in a stadium of people watching cricket
- lora_scale
- 1.03
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 2.16
- output_quality
- 80
- extra_lora_scale
- 0.8
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Bappa playing cricket . Backdrop is in a stadium of people watching cricket ", "lora_scale": 1.03, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 2.16, "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 enkey08/ganpatibappa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", { input: { model: "dev", prompt: "Bappa playing cricket . Backdrop is in a stadium of people watching cricket ", lora_scale: 1.03, num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", guidance_scale: 2.16, 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 enkey08/ganpatibappa using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", input={ "model": "dev", "prompt": "Bappa playing cricket . Backdrop is in a stadium of people watching cricket ", "lora_scale": 1.03, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 2.16, "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 enkey08/ganpatibappa 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": "enkey08/ganpatibappa:99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41", "input": { "model": "dev", "prompt": "Bappa playing cricket . Backdrop is in a stadium of people watching cricket ", "lora_scale": 1.03, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 2.16, "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": "2024-09-01T09:24:42.273789Z", "created_at": "2024-09-01T09:24:24.339000Z", "data_removed": false, "error": null, "id": "dr8kth2yjdrm60chnkka46vmhr", "input": { "model": "dev", "prompt": "Bappa playing cricket . Backdrop is in a stadium of people watching cricket ", "lora_scale": 1.03, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 2.16, "output_quality": 80, "extra_lora_scale": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 32829\nPrompt: Bappa playing cricket . Backdrop is in a stadium of people watching cricket\ntxt2img mode\nUsing dev model\nfree=9702671331328\nDownloading weights\n2024-09-01T09:24:24Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpf_aushsa/weights url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar\n2024-09-01T09:24:26Z | INFO | [ Complete ] dest=/tmp/tmpf_aushsa/weights size=\"172 MB\" total_elapsed=1.592s url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar\nDownloaded weights in 1.62s\nLoaded LoRAs in 9.56s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.53it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.95it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.74it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.60it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.58it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.56it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.54it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.54it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.53it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.52it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.53it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.53it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.53it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.52it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.53it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.52it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.53it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.52it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.55it/s]", "metrics": { "predict_time": 17.932368608, "total_time": 17.934789 }, "output": [ "https://replicate.delivery/yhqm/8ou1CUEmw6olDFhtj7bKfLmnKuO1M31RExk9fS3FwciaTewmA/out-0.jpg" ], "started_at": "2024-09-01T09:24:24.341420Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/dr8kth2yjdrm60chnkka46vmhr", "cancel": "https://api.replicate.com/v1/predictions/dr8kth2yjdrm60chnkka46vmhr/cancel" }, "version": "99a6928330f2ff47ed6ba9cd5a77a63b527628f07177cb30dc0191ce6d31ab41" }Generated inUsing seed: 32829 Prompt: Bappa playing cricket . Backdrop is in a stadium of people watching cricket txt2img mode Using dev model free=9702671331328 Downloading weights 2024-09-01T09:24:24Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpf_aushsa/weights url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar 2024-09-01T09:24:26Z | INFO | [ Complete ] dest=/tmp/tmpf_aushsa/weights size="172 MB" total_elapsed=1.592s url=https://replicate.delivery/yhqm/zPNQ5mHVRe1FFiDeI7vN9x8uqP5zfEnHqkbUwFFVJjpzqnsmA/trained_model.tar Downloaded weights in 1.62s Loaded LoRAs in 9.56s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.53it/s] 7%|▋ | 2/28 [00:00<00:06, 3.95it/s] 11%|█ | 3/28 [00:00<00:06, 3.74it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.60it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.58it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.56it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.54it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.54it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.53it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.52it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.53it/s] 50%|█████ | 14/28 [00:03<00:03, 3.53it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.53it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.52it/s] 61%|██████ | 17/28 [00:04<00:03, 3.53it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.52it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.53it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s] 100%|██████████| 28/28 [00:07<00:00, 3.52it/s] 100%|██████████| 28/28 [00:07<00:00, 3.55it/s]
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