zf-kbot / claymation
Generate clay style images based on prompts or images
- Public
- 487 runs
Prediction
zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4ID1wpx10afwsrgj0cgebev39z5z8StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- A cute girl
- strength
- 0.6
- scheduler
- KarrasDPM
- num_outputs
- 1
- guidance_scale
- 6
- negative_prompt
- ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof
- num_inference_steps
- 24
{ "width": 1024, "height": 1024, "prompt": "A cute girl", "strength": 0.6, "scheduler": "KarrasDPM", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 24 }
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 zf-kbot/claymation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4", { input: { width: 1024, height: 1024, prompt: "A cute girl", strength: 0.6, scheduler: "KarrasDPM", num_outputs: 1, guidance_scale: 6, negative_prompt: "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", num_inference_steps: 24 } } ); // 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 zf-kbot/claymation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4", input={ "width": 1024, "height": 1024, "prompt": "A cute girl", "strength": 0.6, "scheduler": "KarrasDPM", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 24 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run zf-kbot/claymation 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": "zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4", "input": { "width": 1024, "height": 1024, "prompt": "A cute girl", "strength": 0.6, "scheduler": "KarrasDPM", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 24 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-07-02T09:59:15.566949Z", "created_at": "2024-07-02T09:53:44.934000Z", "data_removed": false, "error": null, "id": "1wpx10afwsrgj0cgebev39z5z8", "input": { "width": 1024, "height": 1024, "prompt": "A cute girl", "strength": 0.6, "scheduler": "KarrasDPM", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 24 }, "logs": "Using seed: 5695708\nloading lora file: clay.safetensors lora_scale: 1.0\n 0%| | 0/24 [00:00<?, ?it/s]\n 4%|▍ | 1/24 [00:00<00:09, 2.51it/s]\n 8%|▊ | 2/24 [00:00<00:06, 3.42it/s]\n 12%|█▎ | 3/24 [00:00<00:05, 3.57it/s]\n 17%|█▋ | 4/24 [00:01<00:05, 3.66it/s]\n 21%|██ | 5/24 [00:01<00:05, 3.70it/s]\n 25%|██▌ | 6/24 [00:01<00:04, 3.73it/s]\n 29%|██▉ | 7/24 [00:01<00:04, 3.75it/s]\n 33%|███▎ | 8/24 [00:02<00:04, 3.76it/s]\n 38%|███▊ | 9/24 [00:02<00:03, 3.77it/s]\n 42%|████▏ | 10/24 [00:02<00:03, 3.77it/s]\n 46%|████▌ | 11/24 [00:02<00:03, 3.78it/s]\n 50%|█████ | 12/24 [00:03<00:03, 3.75it/s]\n 54%|█████▍ | 13/24 [00:03<00:02, 3.75it/s]\n 58%|█████▊ | 14/24 [00:03<00:02, 3.80it/s]\n 62%|██████▎ | 15/24 [00:04<00:02, 3.79it/s]\n 67%|██████▋ | 16/24 [00:04<00:02, 3.77it/s]\n 71%|███████ | 17/24 [00:04<00:01, 3.78it/s]\n 75%|███████▌ | 18/24 [00:04<00:01, 3.79it/s]\n 79%|███████▉ | 19/24 [00:05<00:01, 3.78it/s]\n 83%|████████▎ | 20/24 [00:05<00:01, 3.78it/s]\n 88%|████████▊ | 21/24 [00:05<00:00, 3.77it/s]\n 92%|█████████▏| 22/24 [00:05<00:00, 3.78it/s]\n 96%|█████████▌| 23/24 [00:06<00:00, 3.77it/s]\n100%|██████████| 24/24 [00:06<00:00, 3.77it/s]\n100%|██████████| 24/24 [00:06<00:00, 3.73it/s]", "metrics": { "predict_time": 11.81065053, "total_time": 330.632949 }, "output": [ "https://replicate.delivery/pbxt/edv7RYZROejsvk73gjSLDpdQmfVo7FuoaAXUXuiWte0KXgRMB/out-0.png" ], "started_at": "2024-07-02T09:59:03.756298Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/1wpx10afwsrgj0cgebev39z5z8", "cancel": "https://api.replicate.com/v1/predictions/1wpx10afwsrgj0cgebev39z5z8/cancel" }, "version": "95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4" }
Generated inUsing seed: 5695708 loading lora file: clay.safetensors lora_scale: 1.0 0%| | 0/24 [00:00<?, ?it/s] 4%|▍ | 1/24 [00:00<00:09, 2.51it/s] 8%|▊ | 2/24 [00:00<00:06, 3.42it/s] 12%|█▎ | 3/24 [00:00<00:05, 3.57it/s] 17%|█▋ | 4/24 [00:01<00:05, 3.66it/s] 21%|██ | 5/24 [00:01<00:05, 3.70it/s] 25%|██▌ | 6/24 [00:01<00:04, 3.73it/s] 29%|██▉ | 7/24 [00:01<00:04, 3.75it/s] 33%|███▎ | 8/24 [00:02<00:04, 3.76it/s] 38%|███▊ | 9/24 [00:02<00:03, 3.77it/s] 42%|████▏ | 10/24 [00:02<00:03, 3.77it/s] 46%|████▌ | 11/24 [00:02<00:03, 3.78it/s] 50%|█████ | 12/24 [00:03<00:03, 3.75it/s] 54%|█████▍ | 13/24 [00:03<00:02, 3.75it/s] 58%|█████▊ | 14/24 [00:03<00:02, 3.80it/s] 62%|██████▎ | 15/24 [00:04<00:02, 3.79it/s] 67%|██████▋ | 16/24 [00:04<00:02, 3.77it/s] 71%|███████ | 17/24 [00:04<00:01, 3.78it/s] 75%|███████▌ | 18/24 [00:04<00:01, 3.79it/s] 79%|███████▉ | 19/24 [00:05<00:01, 3.78it/s] 83%|████████▎ | 20/24 [00:05<00:01, 3.78it/s] 88%|████████▊ | 21/24 [00:05<00:00, 3.77it/s] 92%|█████████▏| 22/24 [00:05<00:00, 3.78it/s] 96%|█████████▌| 23/24 [00:06<00:00, 3.77it/s] 100%|██████████| 24/24 [00:06<00:00, 3.77it/s] 100%|██████████| 24/24 [00:06<00:00, 3.73it/s]
Prediction
zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4ID78zmx3axvhrgp0cgebhvcwmmxgStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- A girl
- strength
- 0.55
- scheduler
- K_EULER_ANCESTRAL
- num_outputs
- 1
- guidance_scale
- 6
- negative_prompt
- ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof
- num_inference_steps
- 24
{ "image": "https://replicate.delivery/pbxt/LCIgo2duU8JKE1fyRX3JNZdJvgT8CmVhMRlJYjiXHnVioqWP/image4.jpeg", "width": 1024, "height": 1024, "prompt": "A girl", "strength": 0.55, "scheduler": "K_EULER_ANCESTRAL", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 24 }
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 zf-kbot/claymation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4", { input: { image: "https://replicate.delivery/pbxt/LCIgo2duU8JKE1fyRX3JNZdJvgT8CmVhMRlJYjiXHnVioqWP/image4.jpeg", width: 1024, height: 1024, prompt: "A girl", strength: 0.55, scheduler: "K_EULER_ANCESTRAL", num_outputs: 1, guidance_scale: 6, negative_prompt: "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", num_inference_steps: 24 } } ); // 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 zf-kbot/claymation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4", input={ "image": "https://replicate.delivery/pbxt/LCIgo2duU8JKE1fyRX3JNZdJvgT8CmVhMRlJYjiXHnVioqWP/image4.jpeg", "width": 1024, "height": 1024, "prompt": "A girl", "strength": 0.55, "scheduler": "K_EULER_ANCESTRAL", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 24 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run zf-kbot/claymation 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": "zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4", "input": { "image": "https://replicate.delivery/pbxt/LCIgo2duU8JKE1fyRX3JNZdJvgT8CmVhMRlJYjiXHnVioqWP/image4.jpeg", "width": 1024, "height": 1024, "prompt": "A girl", "strength": 0.55, "scheduler": "K_EULER_ANCESTRAL", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 24 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-07-02T10:00:30.125371Z", "created_at": "2024-07-02T10:00:21.724000Z", "data_removed": false, "error": null, "id": "78zmx3axvhrgp0cgebhvcwmmxg", "input": { "image": "https://replicate.delivery/pbxt/LCIgo2duU8JKE1fyRX3JNZdJvgT8CmVhMRlJYjiXHnVioqWP/image4.jpeg", "width": 1024, "height": 1024, "prompt": "A girl", "strength": 0.55, "scheduler": "K_EULER_ANCESTRAL", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 24 }, "logs": "Using seed: 3033138\nloading lora file: clay.safetensors lora_scale: 1.0\n 0%| | 0/13 [00:00<?, ?it/s]\n 8%|▊ | 1/13 [00:00<00:01, 8.45it/s]\n 15%|█▌ | 2/13 [00:00<00:01, 6.16it/s]\n 23%|██▎ | 3/13 [00:00<00:01, 5.67it/s]\n 31%|███ | 4/13 [00:00<00:01, 5.43it/s]\n 38%|███▊ | 5/13 [00:00<00:01, 5.32it/s]\n 46%|████▌ | 6/13 [00:01<00:01, 5.26it/s]\n 54%|█████▍ | 7/13 [00:01<00:01, 5.22it/s]\n 62%|██████▏ | 8/13 [00:01<00:00, 5.20it/s]\n 69%|██████▉ | 9/13 [00:01<00:00, 5.18it/s]\n 77%|███████▋ | 10/13 [00:01<00:00, 5.14it/s]\n 85%|████████▍ | 11/13 [00:02<00:00, 5.13it/s]\n 92%|█████████▏| 12/13 [00:02<00:00, 5.14it/s]\n100%|██████████| 13/13 [00:02<00:00, 5.14it/s]\n100%|██████████| 13/13 [00:02<00:00, 5.29it/s]", "metrics": { "predict_time": 8.355035292, "total_time": 8.401371 }, "output": [ "https://replicate.delivery/pbxt/uYtqgjXGCRY7DdTTL7pZeGfgPjjyE3Xe60F9X5Ro47P5NwImA/out-0.png" ], "started_at": "2024-07-02T10:00:21.770336Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/78zmx3axvhrgp0cgebhvcwmmxg", "cancel": "https://api.replicate.com/v1/predictions/78zmx3axvhrgp0cgebhvcwmmxg/cancel" }, "version": "95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4" }
Generated inUsing seed: 3033138 loading lora file: clay.safetensors lora_scale: 1.0 0%| | 0/13 [00:00<?, ?it/s] 8%|▊ | 1/13 [00:00<00:01, 8.45it/s] 15%|█▌ | 2/13 [00:00<00:01, 6.16it/s] 23%|██▎ | 3/13 [00:00<00:01, 5.67it/s] 31%|███ | 4/13 [00:00<00:01, 5.43it/s] 38%|███▊ | 5/13 [00:00<00:01, 5.32it/s] 46%|████▌ | 6/13 [00:01<00:01, 5.26it/s] 54%|█████▍ | 7/13 [00:01<00:01, 5.22it/s] 62%|██████▏ | 8/13 [00:01<00:00, 5.20it/s] 69%|██████▉ | 9/13 [00:01<00:00, 5.18it/s] 77%|███████▋ | 10/13 [00:01<00:00, 5.14it/s] 85%|████████▍ | 11/13 [00:02<00:00, 5.13it/s] 92%|█████████▏| 12/13 [00:02<00:00, 5.14it/s] 100%|██████████| 13/13 [00:02<00:00, 5.14it/s] 100%|██████████| 13/13 [00:02<00:00, 5.29it/s]
Prediction
zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4IDeej68faw4drgm0cgebm8n5fgjmStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- A cute girl in chair
- strength
- 0.55
- scheduler
- K_EULER_ANCESTRAL
- num_outputs
- 1
- guidance_scale
- 6
- negative_prompt
- ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "A cute girl in chair", "strength": 0.55, "scheduler": "K_EULER_ANCESTRAL", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 30 }
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 zf-kbot/claymation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4", { input: { width: 1024, height: 1024, prompt: "A cute girl in chair", strength: 0.55, scheduler: "K_EULER_ANCESTRAL", num_outputs: 1, guidance_scale: 6, negative_prompt: "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", num_inference_steps: 30 } } ); // 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 zf-kbot/claymation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4", input={ "width": 1024, "height": 1024, "prompt": "A cute girl in chair", "strength": 0.55, "scheduler": "K_EULER_ANCESTRAL", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 30 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run zf-kbot/claymation 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": "zf-kbot/claymation:95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4", "input": { "width": 1024, "height": 1024, "prompt": "A cute girl in chair", "strength": 0.55, "scheduler": "K_EULER_ANCESTRAL", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-07-02T10:06:00.016713Z", "created_at": "2024-07-02T10:05:48.963000Z", "data_removed": false, "error": null, "id": "eej68faw4drgm0cgebm8n5fgjm", "input": { "width": 1024, "height": 1024, "prompt": "A cute girl in chair", "strength": 0.55, "scheduler": "K_EULER_ANCESTRAL", "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, disfigured, duplicate, mutated, bad art, blur, blurry, dof", "num_inference_steps": 30 }, "logs": "Using seed: 13856182\nloading lora file: clay.safetensors lora_scale: 1.0\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:03, 8.48it/s]\n 7%|▋ | 2/30 [00:00<00:04, 6.15it/s]\n 10%|█ | 3/30 [00:00<00:04, 5.66it/s]\n 13%|█▎ | 4/30 [00:00<00:04, 5.46it/s]\n 17%|█▋ | 5/30 [00:00<00:04, 5.34it/s]\n 20%|██ | 6/30 [00:01<00:04, 5.26it/s]\n 23%|██▎ | 7/30 [00:01<00:04, 5.22it/s]\n 27%|██▋ | 8/30 [00:01<00:04, 5.20it/s]\n 30%|███ | 9/30 [00:01<00:04, 5.20it/s]\n 33%|███▎ | 10/30 [00:01<00:03, 5.20it/s]\n 37%|███▋ | 11/30 [00:02<00:03, 5.20it/s]\n 40%|████ | 12/30 [00:02<00:03, 5.15it/s]\n 43%|████▎ | 13/30 [00:02<00:03, 5.18it/s]\n 47%|████▋ | 14/30 [00:02<00:03, 5.18it/s]\n 50%|█████ | 15/30 [00:02<00:02, 5.18it/s]\n 53%|█████▎ | 16/30 [00:03<00:02, 5.17it/s]\n 57%|█████▋ | 17/30 [00:03<00:02, 5.17it/s]\n 60%|██████ | 18/30 [00:03<00:02, 5.17it/s]\n 63%|██████▎ | 19/30 [00:03<00:02, 5.17it/s]\n 67%|██████▋ | 20/30 [00:03<00:01, 5.17it/s]\n 70%|███████ | 21/30 [00:03<00:01, 5.10it/s]\n 73%|███████▎ | 22/30 [00:04<00:01, 5.18it/s]\n 77%|███████▋ | 23/30 [00:04<00:01, 5.18it/s]\n 80%|████████ | 24/30 [00:04<00:01, 5.17it/s]\n 83%|████████▎ | 25/30 [00:04<00:00, 5.17it/s]\n 87%|████████▋ | 26/30 [00:04<00:00, 5.16it/s]\n 90%|█████████ | 27/30 [00:05<00:00, 5.16it/s]\n 93%|█████████▎| 28/30 [00:05<00:00, 5.17it/s]\n 97%|█████████▋| 29/30 [00:05<00:00, 5.16it/s]\n100%|██████████| 30/30 [00:05<00:00, 5.16it/s]\n100%|██████████| 30/30 [00:05<00:00, 5.23it/s]", "metrics": { "predict_time": 11.005196958, "total_time": 11.053713 }, "output": [ "https://replicate.delivery/pbxt/303gNDHZXq6ML5xgEwQANk8pKeI7C87edzDExQv6z5YGMYETA/out-0.png" ], "started_at": "2024-07-02T10:05:49.011516Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/eej68faw4drgm0cgebm8n5fgjm", "cancel": "https://api.replicate.com/v1/predictions/eej68faw4drgm0cgebm8n5fgjm/cancel" }, "version": "95cb01c3e941a760c360946a79d35dba8216b7c5f566f5b9713749414c3030b4" }
Generated inUsing seed: 13856182 loading lora file: clay.safetensors lora_scale: 1.0 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:03, 8.48it/s] 7%|▋ | 2/30 [00:00<00:04, 6.15it/s] 10%|█ | 3/30 [00:00<00:04, 5.66it/s] 13%|█▎ | 4/30 [00:00<00:04, 5.46it/s] 17%|█▋ | 5/30 [00:00<00:04, 5.34it/s] 20%|██ | 6/30 [00:01<00:04, 5.26it/s] 23%|██▎ | 7/30 [00:01<00:04, 5.22it/s] 27%|██▋ | 8/30 [00:01<00:04, 5.20it/s] 30%|███ | 9/30 [00:01<00:04, 5.20it/s] 33%|███▎ | 10/30 [00:01<00:03, 5.20it/s] 37%|███▋ | 11/30 [00:02<00:03, 5.20it/s] 40%|████ | 12/30 [00:02<00:03, 5.15it/s] 43%|████▎ | 13/30 [00:02<00:03, 5.18it/s] 47%|████▋ | 14/30 [00:02<00:03, 5.18it/s] 50%|█████ | 15/30 [00:02<00:02, 5.18it/s] 53%|█████▎ | 16/30 [00:03<00:02, 5.17it/s] 57%|█████▋ | 17/30 [00:03<00:02, 5.17it/s] 60%|██████ | 18/30 [00:03<00:02, 5.17it/s] 63%|██████▎ | 19/30 [00:03<00:02, 5.17it/s] 67%|██████▋ | 20/30 [00:03<00:01, 5.17it/s] 70%|███████ | 21/30 [00:03<00:01, 5.10it/s] 73%|███████▎ | 22/30 [00:04<00:01, 5.18it/s] 77%|███████▋ | 23/30 [00:04<00:01, 5.18it/s] 80%|████████ | 24/30 [00:04<00:01, 5.17it/s] 83%|████████▎ | 25/30 [00:04<00:00, 5.17it/s] 87%|████████▋ | 26/30 [00:04<00:00, 5.16it/s] 90%|█████████ | 27/30 [00:05<00:00, 5.16it/s] 93%|█████████▎| 28/30 [00:05<00:00, 5.17it/s] 97%|█████████▋| 29/30 [00:05<00:00, 5.16it/s] 100%|██████████| 30/30 [00:05<00:00, 5.16it/s] 100%|██████████| 30/30 [00:05<00:00, 5.23it/s]
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