andrei907 / andre
- Public
- 206 runs
-
H100
Prediction
andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50IDq5c8jzeyvnrme0cmey08acbegrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 replicate
Import 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 andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", { input: { model: "dev", prompt: "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", 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 replicate
Import the client:import replicate
Run andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", input={ "model": "dev", "prompt": "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run andrei907/andre 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": "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", "input": { "model": "dev", "prompt": "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-18T03:42:09.692230Z", "created_at": "2025-01-18T03:42:01.949000Z", "data_removed": false, "error": null, "id": "q5c8jzeyvnrme0cmey08acbegr", "input": { "model": "dev", "prompt": "andre înconjurat de cascade care curg în gol, peisaj de fantezie uluitor", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-18 03:42:03.181 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 03:42:03.182 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 90%|████████▉ | 273/304 [00:00<00:00, 2721.90it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.06it/s]\n2025-01-18 03:42:03.297 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\n2025-01-18 03:42:03.298 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f\n2025-01-18 03:42:03.414 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-18 03:42:03.414 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 03:42:03.414 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 90%|████████▉ | 273/304 [00:00<00:00, 2723.24it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.56it/s]\n2025-01-18 03:42:03.529 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 22898\n0it [00:00, ?it/s]\n1it [00:00, 8.33it/s]\n2it [00:00, 5.80it/s]\n3it [00:00, 5.28it/s]\n4it [00:00, 5.07it/s]\n5it [00:00, 4.91it/s]\n6it [00:01, 4.81it/s]\n7it [00:01, 4.77it/s]\n8it [00:01, 4.76it/s]\n9it [00:01, 4.75it/s]\n10it [00:02, 4.71it/s]\n11it [00:02, 4.70it/s]\n12it [00:02, 4.71it/s]\n13it [00:02, 4.71it/s]\n14it [00:02, 4.71it/s]\n15it [00:03, 4.69it/s]\n16it [00:03, 4.67it/s]\n17it [00:03, 4.69it/s]\n18it [00:03, 4.70it/s]\n19it [00:03, 4.70it/s]\n20it [00:04, 4.68it/s]\n21it [00:04, 4.68it/s]\n22it [00:04, 4.68it/s]\n23it [00:04, 4.69it/s]\n24it [00:05, 4.70it/s]\n25it [00:05, 4.69it/s]\n26it [00:05, 4.69it/s]\n27it [00:05, 4.71it/s]\n28it [00:05, 4.72it/s]\n28it [00:05, 4.78it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 6.509387928, "total_time": 7.74323 }, "output": [ "https://replicate.delivery/xezq/pGvzlU4W7r4PMdQauVyTfedbxUpxmNIo0goAcKUEWdURUNGUA/out-0.jpg" ], "started_at": "2025-01-18T03:42:03.182842Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-auanrsobdilal7imeolfweim25fiqlfx63uhegsvwz4xzszxl5mq", "get": "https://api.replicate.com/v1/predictions/q5c8jzeyvnrme0cmey08acbegr", "cancel": "https://api.replicate.com/v1/predictions/q5c8jzeyvnrme0cmey08acbegr/cancel" }, "version": "91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50" }
Generated in2025-01-18 03:42:03.181 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 03:42:03.182 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 90%|████████▉ | 273/304 [00:00<00:00, 2721.90it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.06it/s] 2025-01-18 03:42:03.297 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s 2025-01-18 03:42:03.298 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f 2025-01-18 03:42:03.414 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-18 03:42:03.414 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 03:42:03.414 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 90%|████████▉ | 273/304 [00:00<00:00, 2723.24it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.56it/s] 2025-01-18 03:42:03.529 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s Using seed: 22898 0it [00:00, ?it/s] 1it [00:00, 8.33it/s] 2it [00:00, 5.80it/s] 3it [00:00, 5.28it/s] 4it [00:00, 5.07it/s] 5it [00:00, 4.91it/s] 6it [00:01, 4.81it/s] 7it [00:01, 4.77it/s] 8it [00:01, 4.76it/s] 9it [00:01, 4.75it/s] 10it [00:02, 4.71it/s] 11it [00:02, 4.70it/s] 12it [00:02, 4.71it/s] 13it [00:02, 4.71it/s] 14it [00:02, 4.71it/s] 15it [00:03, 4.69it/s] 16it [00:03, 4.67it/s] 17it [00:03, 4.69it/s] 18it [00:03, 4.70it/s] 19it [00:03, 4.70it/s] 20it [00:04, 4.68it/s] 21it [00:04, 4.68it/s] 22it [00:04, 4.68it/s] 23it [00:04, 4.69it/s] 24it [00:05, 4.70it/s] 25it [00:05, 4.69it/s] 26it [00:05, 4.69it/s] 27it [00:05, 4.71it/s] 28it [00:05, 4.72it/s] 28it [00:05, 4.78it/s] Total safe images: 1 out of 1
Prediction
andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50IDry7vzrqfesrmc0cmf6jsvr2hmrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 replicate
Import 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 andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", { input: { model: "dev", prompt: "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", 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 replicate
Import the client:import replicate
Run andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", input={ "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run andrei907/andre 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": "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", "input": { "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-18T13:41:53.802312Z", "created_at": "2025-01-18T13:41:45.462000Z", "data_removed": false, "error": null, "id": "ry7vzrqfesrmc0cmf6jsvr2hmr", "input": { "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-18 13:41:45.793 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 13:41:45.794 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2793.55it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2673.59it/s]\n2025-01-18 13:41:45.908 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=30216265678848\nDownloading weights\n2025-01-18T13:41:45Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpwupodji5/weights url=https://replicate.delivery/xezq/Af7Nlq6uGzS1TCzIAs6zLVvpKBQR0i6zXfhq3o0EXXiawMGUA/trained_model.tar\n2025-01-18T13:41:47Z | INFO | [ Complete ] dest=/tmp/tmpwupodji5/weights size=\"172 MB\" total_elapsed=1.600s url=https://replicate.delivery/xezq/Af7Nlq6uGzS1TCzIAs6zLVvpKBQR0i6zXfhq3o0EXXiawMGUA/trained_model.tar\nDownloaded weights in 1.62s\n2025-01-18 13:41:47.531 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f\n2025-01-18 13:41:47.602 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-18 13:41:47.602 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 13:41:47.602 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2798.48it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2678.18it/s]\n2025-01-18 13:41:47.716 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 37567\n0it [00:00, ?it/s]\n1it [00:00, 8.35it/s]\n2it [00:00, 5.83it/s]\n3it [00:00, 5.32it/s]\n4it [00:00, 5.11it/s]\n5it [00:00, 4.98it/s]\n6it [00:01, 4.89it/s]\n7it [00:01, 4.84it/s]\n8it [00:01, 4.82it/s]\n9it [00:01, 4.81it/s]\n10it [00:02, 4.78it/s]\n11it [00:02, 4.77it/s]\n12it [00:02, 4.77it/s]\n13it [00:02, 4.78it/s]\n14it [00:02, 4.79it/s]\n15it [00:03, 4.77it/s]\n16it [00:03, 4.76it/s]\n17it [00:03, 4.76it/s]\n18it [00:03, 4.77it/s]\n19it [00:03, 4.77it/s]\n20it [00:04, 4.76it/s]\n21it [00:04, 4.75it/s]\n22it [00:04, 4.75it/s]\n23it [00:04, 4.76it/s]\n24it [00:04, 4.76it/s]\n25it [00:05, 4.76it/s]\n26it [00:05, 4.75it/s]\n27it [00:05, 4.75it/s]\n28it [00:05, 4.75it/s]\n28it [00:05, 4.84it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 8.007675693, "total_time": 8.340312 }, "output": [ "https://replicate.delivery/xezq/UarhCUYTuG5fEyoCsizMNO0YZCLtskDNj4H8qW51WkhQDLDKA/out-0.jpg" ], "started_at": "2025-01-18T13:41:45.794637Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-ylhtkthtukdpjos753y3iek7o7vslwhhwd4iq6e53mghs5pz3wtq", "get": "https://api.replicate.com/v1/predictions/ry7vzrqfesrmc0cmf6jsvr2hmr", "cancel": "https://api.replicate.com/v1/predictions/ry7vzrqfesrmc0cmf6jsvr2hmr/cancel" }, "version": "91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50" }
Generated in2025-01-18 13:41:45.793 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 13:41:45.794 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2793.55it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2673.59it/s] 2025-01-18 13:41:45.908 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=30216265678848 Downloading weights 2025-01-18T13:41:45Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpwupodji5/weights url=https://replicate.delivery/xezq/Af7Nlq6uGzS1TCzIAs6zLVvpKBQR0i6zXfhq3o0EXXiawMGUA/trained_model.tar 2025-01-18T13:41:47Z | INFO | [ Complete ] dest=/tmp/tmpwupodji5/weights size="172 MB" total_elapsed=1.600s url=https://replicate.delivery/xezq/Af7Nlq6uGzS1TCzIAs6zLVvpKBQR0i6zXfhq3o0EXXiawMGUA/trained_model.tar Downloaded weights in 1.62s 2025-01-18 13:41:47.531 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f 2025-01-18 13:41:47.602 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-18 13:41:47.602 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 13:41:47.602 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2798.48it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2678.18it/s] 2025-01-18 13:41:47.716 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s Using seed: 37567 0it [00:00, ?it/s] 1it [00:00, 8.35it/s] 2it [00:00, 5.83it/s] 3it [00:00, 5.32it/s] 4it [00:00, 5.11it/s] 5it [00:00, 4.98it/s] 6it [00:01, 4.89it/s] 7it [00:01, 4.84it/s] 8it [00:01, 4.82it/s] 9it [00:01, 4.81it/s] 10it [00:02, 4.78it/s] 11it [00:02, 4.77it/s] 12it [00:02, 4.77it/s] 13it [00:02, 4.78it/s] 14it [00:02, 4.79it/s] 15it [00:03, 4.77it/s] 16it [00:03, 4.76it/s] 17it [00:03, 4.76it/s] 18it [00:03, 4.77it/s] 19it [00:03, 4.77it/s] 20it [00:04, 4.76it/s] 21it [00:04, 4.75it/s] 22it [00:04, 4.75it/s] 23it [00:04, 4.76it/s] 24it [00:04, 4.76it/s] 25it [00:05, 4.76it/s] 26it [00:05, 4.75it/s] 27it [00:05, 4.75it/s] 28it [00:05, 4.75it/s] 28it [00:05, 4.84it/s] Total safe images: 1 out of 1
Prediction
andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50IDvqn5y6rqzxrma0cmf6ktf5gp0gStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 replicate
Import 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 andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", { input: { model: "dev", prompt: "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", 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 replicate
Import the client:import replicate
Run andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", input={ "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run andrei907/andre 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": "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", "input": { "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-18T13:43:08.316074Z", "created_at": "2025-01-18T13:43:01.375000Z", "data_removed": false, "error": null, "id": "vqn5y6rqzxrma0cmf6ktf5gp0g", "input": { "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-18 13:43:01.924 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 13:43:01.925 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2729.10it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.23it/s]\n2025-01-18 13:43:02.040 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\n2025-01-18 13:43:02.041 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f\n2025-01-18 13:43:02.155 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-18 13:43:02.155 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 13:43:02.155 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2724.62it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2649.05it/s]\n2025-01-18 13:43:02.270 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 19416\n0it [00:00, ?it/s]\n1it [00:00, 8.39it/s]\n2it [00:00, 5.86it/s]\n3it [00:00, 5.34it/s]\n4it [00:00, 5.13it/s]\n5it [00:00, 5.01it/s]\n6it [00:01, 4.91it/s]\n7it [00:01, 4.88it/s]\n8it [00:01, 4.87it/s]\n9it [00:01, 4.85it/s]\n10it [00:01, 4.83it/s]\n11it [00:02, 4.80it/s]\n12it [00:02, 4.80it/s]\n13it [00:02, 4.81it/s]\n14it [00:02, 4.81it/s]\n15it [00:03, 4.81it/s]\n16it [00:03, 4.79it/s]\n17it [00:03, 4.79it/s]\n18it [00:03, 4.79it/s]\n19it [00:03, 4.80it/s]\n20it [00:04, 4.80it/s]\n21it [00:04, 4.79it/s]\n22it [00:04, 4.80it/s]\n23it [00:04, 4.80it/s]\n24it [00:04, 4.80it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.80it/s]\n27it [00:05, 4.79it/s]\n28it [00:05, 4.79it/s]\n28it [00:05, 4.87it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 6.390183811, "total_time": 6.941074 }, "output": [ "https://replicate.delivery/xezq/nGApe0sPPeh1BUrEzbMKghf7ZnZFCfOZh7YNb05ZugDyewygC/out-0.jpg" ], "started_at": "2025-01-18T13:43:01.925890Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-kdnvayzm4im5vsav6pwivmroerlfnrmgsrzmc4u4zpfeugha5m6q", "get": "https://api.replicate.com/v1/predictions/vqn5y6rqzxrma0cmf6ktf5gp0g", "cancel": "https://api.replicate.com/v1/predictions/vqn5y6rqzxrma0cmf6ktf5gp0g/cancel" }, "version": "91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50" }
Generated in2025-01-18 13:43:01.924 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 13:43:01.925 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2729.10it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2653.23it/s] 2025-01-18 13:43:02.040 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s 2025-01-18 13:43:02.041 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f 2025-01-18 13:43:02.155 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-18 13:43:02.155 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 13:43:02.155 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2724.62it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2649.05it/s] 2025-01-18 13:43:02.270 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s Using seed: 19416 0it [00:00, ?it/s] 1it [00:00, 8.39it/s] 2it [00:00, 5.86it/s] 3it [00:00, 5.34it/s] 4it [00:00, 5.13it/s] 5it [00:00, 5.01it/s] 6it [00:01, 4.91it/s] 7it [00:01, 4.88it/s] 8it [00:01, 4.87it/s] 9it [00:01, 4.85it/s] 10it [00:01, 4.83it/s] 11it [00:02, 4.80it/s] 12it [00:02, 4.80it/s] 13it [00:02, 4.81it/s] 14it [00:02, 4.81it/s] 15it [00:03, 4.81it/s] 16it [00:03, 4.79it/s] 17it [00:03, 4.79it/s] 18it [00:03, 4.79it/s] 19it [00:03, 4.80it/s] 20it [00:04, 4.80it/s] 21it [00:04, 4.79it/s] 22it [00:04, 4.80it/s] 23it [00:04, 4.80it/s] 24it [00:04, 4.80it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.80it/s] 27it [00:05, 4.79it/s] 28it [00:05, 4.79it/s] 28it [00:05, 4.87it/s] Total safe images: 1 out of 1
Prediction
andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50ID94dfyvspw9rma0cmf6ptjpa67gStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "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 replicate
Import 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 andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", { input: { model: "dev", prompt: "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", 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 replicate
Import the client:import replicate
Run andrei907/andre using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", input={ "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run andrei907/andre 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": "andrei907/andre:91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50", "input": { "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-18T13:49:48.885643Z", "created_at": "2025-01-18T13:49:42.498000Z", "data_removed": false, "error": null, "id": "94dfyvspw9rma0cmf6ptjpa67g", "input": { "model": "dev", "prompt": "andre as a confident and modern individual, dressed in sleek professional attire, illuminated by vibrant neon city lights. The setting features a futuristic urban skyline in the background. [KEYWORD] is holding a glowing high-tech gadget, exuding intelligence and determination, cinematic lighting, ultra-realistic details, --ar 9:16 --v 5.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-18 13:49:42.528 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 13:49:42.528 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 90%|█████████ | 274/304 [00:00<00:00, 2725.61it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2625.14it/s]\n2025-01-18 13:49:42.644 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\n2025-01-18 13:49:42.646 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f\n2025-01-18 13:49:42.757 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-18 13:49:42.757 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-18 13:49:42.757 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 90%|█████████ | 274/304 [00:00<00:00, 2732.13it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2631.44it/s]\n2025-01-18 13:49:42.873 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s\nUsing seed: 28504\n0it [00:00, ?it/s]\n1it [00:00, 8.38it/s]\n2it [00:00, 5.87it/s]\n3it [00:00, 5.36it/s]\n4it [00:00, 5.15it/s]\n5it [00:00, 5.03it/s]\n6it [00:01, 4.94it/s]\n7it [00:01, 4.90it/s]\n8it [00:01, 4.88it/s]\n9it [00:01, 4.87it/s]\n10it [00:01, 4.87it/s]\n11it [00:02, 4.85it/s]\n12it [00:02, 4.84it/s]\n13it [00:02, 4.83it/s]\n14it [00:02, 4.83it/s]\n15it [00:03, 4.83it/s]\n16it [00:03, 4.83it/s]\n17it [00:03, 4.82it/s]\n18it [00:03, 4.82it/s]\n19it [00:03, 4.83it/s]\n20it [00:04, 4.82it/s]\n21it [00:04, 4.81it/s]\n22it [00:04, 4.81it/s]\n23it [00:04, 4.81it/s]\n24it [00:04, 4.81it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.82it/s]\n27it [00:05, 4.82it/s]\n28it [00:05, 4.81it/s]\n28it [00:05, 4.90it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 6.356605624, "total_time": 6.387643 }, "output": [ "https://replicate.delivery/xezq/89RKWYtG7eR3BSrJkbFQz5x7VnHaG32uWNKwJ1a14xYeNWGUA/out-0.jpg" ], "started_at": "2025-01-18T13:49:42.529038Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-l22uwqvmettnuulsonjs2ty222ezu66jd7fgefavpvyemtcywh4q", "get": "https://api.replicate.com/v1/predictions/94dfyvspw9rma0cmf6ptjpa67g", "cancel": "https://api.replicate.com/v1/predictions/94dfyvspw9rma0cmf6ptjpa67g/cancel" }, "version": "91c7f8f5d910f169d295cdc12d9dfcc6ead290e93b3172a9e70dcc6b20910e50" }
Generated in2025-01-18 13:49:42.528 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 13:49:42.528 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 90%|█████████ | 274/304 [00:00<00:00, 2725.61it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2625.14it/s] 2025-01-18 13:49:42.644 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s 2025-01-18 13:49:42.646 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5b32327e723ba22f 2025-01-18 13:49:42.757 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-18 13:49:42.757 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-18 13:49:42.757 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 90%|█████████ | 274/304 [00:00<00:00, 2732.13it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2631.44it/s] 2025-01-18 13:49:42.873 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.23s Using seed: 28504 0it [00:00, ?it/s] 1it [00:00, 8.38it/s] 2it [00:00, 5.87it/s] 3it [00:00, 5.36it/s] 4it [00:00, 5.15it/s] 5it [00:00, 5.03it/s] 6it [00:01, 4.94it/s] 7it [00:01, 4.90it/s] 8it [00:01, 4.88it/s] 9it [00:01, 4.87it/s] 10it [00:01, 4.87it/s] 11it [00:02, 4.85it/s] 12it [00:02, 4.84it/s] 13it [00:02, 4.83it/s] 14it [00:02, 4.83it/s] 15it [00:03, 4.83it/s] 16it [00:03, 4.83it/s] 17it [00:03, 4.82it/s] 18it [00:03, 4.82it/s] 19it [00:03, 4.83it/s] 20it [00:04, 4.82it/s] 21it [00:04, 4.81it/s] 22it [00:04, 4.81it/s] 23it [00:04, 4.81it/s] 24it [00:04, 4.81it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.82it/s] 27it [00:05, 4.82it/s] 28it [00:05, 4.81it/s] 28it [00:05, 4.90it/s] Total safe images: 1 out of 1
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