ozcancelik / ataturk
High-quality Flux model trained on historical photographs of Mustafa Kemal Atatürk. Use "ATATURK" for trigger.
- Public
- 129 runs
-
H100
Prediction
ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33IDm57hcp3p51rma0ckdwd8qa7p34StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Hyperrealistic portrait of ATATURK, 40 years old, looking and smiling, medium shot
- 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": "Hyperrealistic portrait of ATATURK, 40 years old, looking and smiling, medium shot", "go_fast": true, "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 ozcancelik/ataturk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", { input: { model: "dev", prompt: "Hyperrealistic portrait of ATATURK, 40 years old, looking and smiling, medium shot", go_fast: true, 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 ozcancelik/ataturk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", input={ "model": "dev", "prompt": "Hyperrealistic portrait of ATATURK, 40 years old, looking and smiling, medium shot", "go_fast": True, "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 ozcancelik/ataturk 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": "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", "input": { "model": "dev", "prompt": "Hyperrealistic portrait of ATATURK, 40 years old, looking and smiling, medium shot", "go_fast": true, "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.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/ozcancelik/ataturk@sha256:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33 \ -i 'model="dev"' \ -i 'prompt="Hyperrealistic portrait of ATATURK, 40 years old, looking and smiling, medium shot"' \ -i 'go_fast=true' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/ozcancelik/ataturk@sha256:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "Hyperrealistic portrait of ATATURK, 40 years old, looking and smiling, medium shot", "go_fast": true, "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 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-11-27T19:30:28.367126Z", "created_at": "2024-11-27T19:30:25.448000Z", "data_removed": false, "error": null, "id": "m57hcp3p51rma0ckdwd8qa7p34", "input": { "model": "dev", "prompt": "Hyperrealistic portrait of ATATURK, 40 years old, looking and smiling, medium shot", "go_fast": true, "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": "Lora https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar already loaded\nrunning quantized prediction\nUsing seed: 987801278\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 16.71it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 12.48it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 11.53it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.13it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 10.90it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 10.46it/s]\n 50%|█████ | 14/28 [00:01<00:01, 10.47it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 10.48it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 10.48it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 10.46it/s]\n 79%|███████▊ | 22/28 [00:02<00:00, 10.33it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 10.34it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 10.38it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.42it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.68it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 2.910533132, "total_time": 2.919126 }, "output": [ "https://replicate.delivery/xezq/qpeIW5Kf52hsakqLa8FmbJd6Ggil8ISJjGzl4KpPoX9UVS1TA/out-0.webp" ], "started_at": "2024-11-27T19:30:25.456593Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-zhd2shhhaoegldsuh2aeo6er664zep4au3r6k5vdojphvjg4adga", "get": "https://api.replicate.com/v1/predictions/m57hcp3p51rma0ckdwd8qa7p34", "cancel": "https://api.replicate.com/v1/predictions/m57hcp3p51rma0ckdwd8qa7p34/cancel" }, "version": "2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33" }Generated inLora https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar already loaded running quantized prediction Using seed: 987801278 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 16.71it/s] 14%|█▍ | 4/28 [00:00<00:01, 12.48it/s] 21%|██▏ | 6/28 [00:00<00:01, 11.53it/s] 29%|██▊ | 8/28 [00:00<00:01, 11.13it/s] 36%|███▌ | 10/28 [00:00<00:01, 10.90it/s] 43%|████▎ | 12/28 [00:01<00:01, 10.46it/s] 50%|█████ | 14/28 [00:01<00:01, 10.47it/s] 57%|█████▋ | 16/28 [00:01<00:01, 10.48it/s] 64%|██████▍ | 18/28 [00:01<00:00, 10.48it/s] 71%|███████▏ | 20/28 [00:01<00:00, 10.46it/s] 79%|███████▊ | 22/28 [00:02<00:00, 10.33it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.34it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.38it/s] 100%|██████████| 28/28 [00:02<00:00, 10.42it/s] 100%|██████████| 28/28 [00:02<00:00, 10.68it/s] Total safe images: 1 out of 1Prediction
ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33IDckdxqkrhmsrmc0ckdwnr99p40mStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Hyperrealistic portrait of ATATURK, 40 years old, looking and pointing at viewer and smiling, blue eyes, medium shot
- 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": "Hyperrealistic portrait of ATATURK, 40 years old, looking and pointing at viewer and smiling, blue eyes, medium shot", "go_fast": true, "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 ozcancelik/ataturk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", { input: { model: "dev", prompt: "Hyperrealistic portrait of ATATURK, 40 years old, looking and pointing at viewer and smiling, blue eyes, medium shot", go_fast: true, 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 ozcancelik/ataturk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", input={ "model": "dev", "prompt": "Hyperrealistic portrait of ATATURK, 40 years old, looking and pointing at viewer and smiling, blue eyes, medium shot", "go_fast": True, "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 ozcancelik/ataturk 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": "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", "input": { "model": "dev", "prompt": "Hyperrealistic portrait of ATATURK, 40 years old, looking and pointing at viewer and smiling, blue eyes, medium shot", "go_fast": true, "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.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/ozcancelik/ataturk@sha256:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33 \ -i 'model="dev"' \ -i 'prompt="Hyperrealistic portrait of ATATURK, 40 years old, looking and pointing at viewer and smiling, blue eyes, medium shot"' \ -i 'go_fast=true' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/ozcancelik/ataturk@sha256:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "Hyperrealistic portrait of ATATURK, 40 years old, looking and pointing at viewer and smiling, blue eyes, medium shot", "go_fast": true, "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 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-11-27T19:48:38.747583Z", "created_at": "2024-11-27T19:48:33.830000Z", "data_removed": false, "error": null, "id": "ckdxqkrhmsrmc0ckdwnr99p40m", "input": { "model": "dev", "prompt": "Hyperrealistic portrait of ATATURK, 40 years old, looking and pointing at viewer and smiling, blue eyes, medium shot", "go_fast": true, "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": "2024-11-27 19:48:35.610 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-11-27 19:48:35.611 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13062.75it/s]\n2024-11-27 19:48:35.634 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.024s\n2024-11-27 19:48:35.635 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/65d8046f54478832\n2024-11-27 19:48:35.703 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded\n2024-11-27 19:48:35.703 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-11-27 19:48:35.703 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 41%|████ | 125/304 [00:00<00:00, 1247.62it/s]\nApplying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 983.77it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 966.85it/s]\n2024-11-27 19:48:36.018 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.38s\nrunning quantized prediction\nUsing seed: 3941017020\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 18.49it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 13.58it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 12.49it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 12.04it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.80it/s]\n 43%|████▎ | 12/28 [00:00<00:01, 11.47it/s]\n 50%|█████ | 14/28 [00:01<00:01, 11.41it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 11.42it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 11.44it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 11.43it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 11.34it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 11.27it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 11.28it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.31it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.64it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 3.136093494, "total_time": 4.917583 }, "output": [ "https://replicate.delivery/xezq/dQEINleSvUVJJqKRO2WImQ9xCyTec2xFvgJxfQexbymZZKVPB/out-0.webp" ], "started_at": "2024-11-27T19:48:35.611490Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-yjh5hsfqg542ambtem5kdizwxzc3gys3y5zdesup3gfqmzwbjphq", "get": "https://api.replicate.com/v1/predictions/ckdxqkrhmsrmc0ckdwnr99p40m", "cancel": "https://api.replicate.com/v1/predictions/ckdxqkrhmsrmc0ckdwnr99p40m/cancel" }, "version": "2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33" }Generated in2024-11-27 19:48:35.610 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-11-27 19:48:35.611 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13062.75it/s] 2024-11-27 19:48:35.634 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.024s 2024-11-27 19:48:35.635 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/65d8046f54478832 2024-11-27 19:48:35.703 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded 2024-11-27 19:48:35.703 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-11-27 19:48:35.703 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 41%|████ | 125/304 [00:00<00:00, 1247.62it/s] Applying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 983.77it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 966.85it/s] 2024-11-27 19:48:36.018 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.38s running quantized prediction Using seed: 3941017020 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 18.49it/s] 14%|█▍ | 4/28 [00:00<00:01, 13.58it/s] 21%|██▏ | 6/28 [00:00<00:01, 12.49it/s] 29%|██▊ | 8/28 [00:00<00:01, 12.04it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.80it/s] 43%|████▎ | 12/28 [00:00<00:01, 11.47it/s] 50%|█████ | 14/28 [00:01<00:01, 11.41it/s] 57%|█████▋ | 16/28 [00:01<00:01, 11.42it/s] 64%|██████▍ | 18/28 [00:01<00:00, 11.44it/s] 71%|███████▏ | 20/28 [00:01<00:00, 11.43it/s] 79%|███████▊ | 22/28 [00:01<00:00, 11.34it/s] 86%|████████▌ | 24/28 [00:02<00:00, 11.27it/s] 93%|█████████▎| 26/28 [00:02<00:00, 11.28it/s] 100%|██████████| 28/28 [00:02<00:00, 11.31it/s] 100%|██████████| 28/28 [00:02<00:00, 11.64it/s] Total safe images: 1 out of 1Prediction
ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33IDvnxjnq5hqdrma0ckdws9mgdjhwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.
- 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": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": true, "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 ozcancelik/ataturk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", { input: { model: "dev", prompt: "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", go_fast: true, 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 ozcancelik/ataturk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", input={ "model": "dev", "prompt": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": True, "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 ozcancelik/ataturk 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": "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", "input": { "model": "dev", "prompt": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": true, "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.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/ozcancelik/ataturk@sha256:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33 \ -i 'model="dev"' \ -i 'prompt="ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s."' \ -i 'go_fast=true' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/ozcancelik/ataturk@sha256:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": true, "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 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-11-27T19:57:02.149964Z", "created_at": "2024-11-27T19:56:53.563000Z", "data_removed": false, "error": null, "id": "vnxjnq5hqdrma0ckdws9mgdjhw", "input": { "model": "dev", "prompt": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": true, "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": "2024-11-27 19:56:56.176 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-11-27 19:56:56.176 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 12675.14it/s]\n2024-11-27 19:56:56.201 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.025s\nfree=29190296059904\nDownloading weights\n2024-11-27T19:56:56Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp706rc0bf/weights url=https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar\n2024-11-27T19:56:59Z | INFO | [ Complete ] dest=/tmp/tmp706rc0bf/weights size=\"172 MB\" total_elapsed=2.812s url=https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar\nDownloaded weights in 2.84s\n2024-11-27 19:56:59.046 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/65d8046f54478832\n2024-11-27 19:56:59.119 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded\n2024-11-27 19:56:59.120 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-11-27 19:56:59.120 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 39%|███▉ | 120/304 [00:00<00:00, 1195.44it/s]\nApplying LoRA: 79%|███████▉ | 240/304 [00:00<00:00, 969.21it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 983.12it/s]\n2024-11-27 19:56:59.429 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.38s\nrunning quantized prediction\nUsing seed: 1451321283\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 18.39it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 13.63it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 12.58it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 12.16it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.91it/s]\n 43%|████▎ | 12/28 [00:00<00:01, 11.56it/s]\n 50%|█████ | 14/28 [00:01<00:01, 11.52it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 11.50it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 11.49it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 11.49it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 11.42it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 11.36it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 11.37it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.38it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.71it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 5.972698071, "total_time": 8.586964 }, "output": [ "https://replicate.delivery/xezq/IeH8r7cTz6TesEzB8CeNTtfA5Kbu4QsspMjsiiufRVIwxVqeE/out-0.webp" ], "started_at": "2024-11-27T19:56:56.177266Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-glpz2vkskwsz7acneyjdququedu6nodltpikzjlfritguc3d6kea", "get": "https://api.replicate.com/v1/predictions/vnxjnq5hqdrma0ckdws9mgdjhw", "cancel": "https://api.replicate.com/v1/predictions/vnxjnq5hqdrma0ckdws9mgdjhw/cancel" }, "version": "2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33" }Generated in2024-11-27 19:56:56.176 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-11-27 19:56:56.176 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 12675.14it/s] 2024-11-27 19:56:56.201 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.025s free=29190296059904 Downloading weights 2024-11-27T19:56:56Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp706rc0bf/weights url=https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar 2024-11-27T19:56:59Z | INFO | [ Complete ] dest=/tmp/tmp706rc0bf/weights size="172 MB" total_elapsed=2.812s url=https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar Downloaded weights in 2.84s 2024-11-27 19:56:59.046 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/65d8046f54478832 2024-11-27 19:56:59.119 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded 2024-11-27 19:56:59.120 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-11-27 19:56:59.120 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 39%|███▉ | 120/304 [00:00<00:00, 1195.44it/s] Applying LoRA: 79%|███████▉ | 240/304 [00:00<00:00, 969.21it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 983.12it/s] 2024-11-27 19:56:59.429 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.38s running quantized prediction Using seed: 1451321283 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 18.39it/s] 14%|█▍ | 4/28 [00:00<00:01, 13.63it/s] 21%|██▏ | 6/28 [00:00<00:01, 12.58it/s] 29%|██▊ | 8/28 [00:00<00:01, 12.16it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.91it/s] 43%|████▎ | 12/28 [00:00<00:01, 11.56it/s] 50%|█████ | 14/28 [00:01<00:01, 11.52it/s] 57%|█████▋ | 16/28 [00:01<00:01, 11.50it/s] 64%|██████▍ | 18/28 [00:01<00:00, 11.49it/s] 71%|███████▏ | 20/28 [00:01<00:00, 11.49it/s] 79%|███████▊ | 22/28 [00:01<00:00, 11.42it/s] 86%|████████▌ | 24/28 [00:02<00:00, 11.36it/s] 93%|█████████▎| 26/28 [00:02<00:00, 11.37it/s] 100%|██████████| 28/28 [00:02<00:00, 11.38it/s] 100%|██████████| 28/28 [00:02<00:00, 11.71it/s] Total safe images: 1 out of 1Prediction
ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33IDsqvae68ka9rme0ckdwsr1h643rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.
- 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": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": true, "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 ozcancelik/ataturk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", { input: { model: "dev", prompt: "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", go_fast: true, 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 ozcancelik/ataturk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", input={ "model": "dev", "prompt": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": True, "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 ozcancelik/ataturk 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": "ozcancelik/ataturk:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33", "input": { "model": "dev", "prompt": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": true, "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.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/ozcancelik/ataturk@sha256:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33 \ -i 'model="dev"' \ -i 'prompt="ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s."' \ -i 'go_fast=true' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/ozcancelik/ataturk@sha256:2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": true, "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 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-11-27T19:57:24.437174Z", "created_at": "2024-11-27T19:57:18.546000Z", "data_removed": false, "error": null, "id": "sqvae68ka9rme0ckdwsr1h643r", "input": { "model": "dev", "prompt": "ATATURK is playing with children in a sunny outdoor setting, wearing his iconic light-colored suit. He is smiling warmly while surrounded by happy Turkish children of different ages. Some kids are holding his hands, while others are showing him their books or toys. The scene captures his well-known love for children and education, with a school building visible in the background. The image has a nostalgic, historical quality with soft lighting and warm colors, reminiscent of photographs from the 1930s.", "go_fast": true, "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": "2024-11-27 19:57:18.663 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-11-27 19:57:18.663 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13056.73it/s]\n2024-11-27 19:57:18.687 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.024s\nfree=29316402065408\nDownloading weights\n2024-11-27T19:57:18Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpb_7stbbk/weights url=https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar\n2024-11-27T19:57:21Z | INFO | [ Complete ] dest=/tmp/tmpb_7stbbk/weights size=\"172 MB\" total_elapsed=2.610s url=https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar\nDownloaded weights in 2.64s\n2024-11-27 19:57:21.329 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/65d8046f54478832\n2024-11-27 19:57:21.399 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded\n2024-11-27 19:57:21.400 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys\n2024-11-27 19:57:21.400 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 40%|███▉ | 121/304 [00:00<00:00, 1205.69it/s]\nApplying LoRA: 80%|███████▉ | 242/304 [00:00<00:00, 972.90it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 974.04it/s]\n2024-11-27 19:57:21.712 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.38s\nrunning quantized prediction\nUsing seed: 2614226008\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 18.28it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 13.66it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 12.59it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 12.17it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.89it/s]\n 43%|████▎ | 12/28 [00:00<00:01, 11.49it/s]\n 50%|█████ | 14/28 [00:01<00:01, 11.45it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 11.45it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 11.47it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 11.49it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 11.42it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 11.32it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 11.33it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.39it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.70it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 5.772765966, "total_time": 5.891174 }, "output": [ "https://replicate.delivery/xezq/7xeL4vngEJ1iGqW769R4Sk6IFJcPJLxPDY7iQEch3QaSXp6JA/out-0.webp" ], "started_at": "2024-11-27T19:57:18.664408Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-2gkfx6ts7s3zwclpggbaotoa7lfelmlczu6cl6vftctn6mly3tta", "get": "https://api.replicate.com/v1/predictions/sqvae68ka9rme0ckdwsr1h643r", "cancel": "https://api.replicate.com/v1/predictions/sqvae68ka9rme0ckdwsr1h643r/cancel" }, "version": "2c7216f21800cc0f193757c43d0f6a88cd72efdacbe447f93cf1511e43b2cf33" }Generated in2024-11-27 19:57:18.663 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-11-27 19:57:18.663 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13056.73it/s] 2024-11-27 19:57:18.687 | SUCCESS | fp8.lora_loading:unload_loras:559 - LoRAs unloaded in 0.024s free=29316402065408 Downloading weights 2024-11-27T19:57:18Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpb_7stbbk/weights url=https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar 2024-11-27T19:57:21Z | INFO | [ Complete ] dest=/tmp/tmpb_7stbbk/weights size="172 MB" total_elapsed=2.610s url=https://replicate.delivery/xezq/PEngcF31GYqFGFh3PfjrSe7irryC6AEX2Z8ph9mrfLY6fAVPB/trained_model.tar Downloaded weights in 2.64s 2024-11-27 19:57:21.329 | INFO | fp8.lora_loading:convert_lora_weights:493 - Loading LoRA weights for /src/weights-cache/65d8046f54478832 2024-11-27 19:57:21.399 | INFO | fp8.lora_loading:convert_lora_weights:514 - LoRA weights loaded 2024-11-27 19:57:21.400 | DEBUG | fp8.lora_loading:apply_lora_to_model:569 - Extracting keys 2024-11-27 19:57:21.400 | DEBUG | fp8.lora_loading:apply_lora_to_model:576 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 40%|███▉ | 121/304 [00:00<00:00, 1205.69it/s] Applying LoRA: 80%|███████▉ | 242/304 [00:00<00:00, 972.90it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 974.04it/s] 2024-11-27 19:57:21.712 | SUCCESS | fp8.lora_loading:load_lora:534 - LoRA applied in 0.38s running quantized prediction Using seed: 2614226008 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 18.28it/s] 14%|█▍ | 4/28 [00:00<00:01, 13.66it/s] 21%|██▏ | 6/28 [00:00<00:01, 12.59it/s] 29%|██▊ | 8/28 [00:00<00:01, 12.17it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.89it/s] 43%|████▎ | 12/28 [00:00<00:01, 11.49it/s] 50%|█████ | 14/28 [00:01<00:01, 11.45it/s] 57%|█████▋ | 16/28 [00:01<00:01, 11.45it/s] 64%|██████▍ | 18/28 [00:01<00:00, 11.47it/s] 71%|███████▏ | 20/28 [00:01<00:00, 11.49it/s] 79%|███████▊ | 22/28 [00:01<00:00, 11.42it/s] 86%|████████▌ | 24/28 [00:02<00:00, 11.32it/s] 93%|█████████▎| 26/28 [00:02<00:00, 11.33it/s] 100%|██████████| 28/28 [00:02<00:00, 11.39it/s] 100%|██████████| 28/28 [00:02<00:00, 11.70it/s] Total safe images: 1 out of 1
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