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You're looking at a specific version of this model. Jump to the model overview.
alexgenovese /sdxl-custom-model:a08504bd
This version is disabled.
This version has been disabled because it consistently fails to complete setup.
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=alexgenovese/sdxl-custom-model
or set up a project from scratch
npm install replicateSet the
REPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run alexgenovese/sdxl-custom-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"alexgenovese/sdxl-custom-model:a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff",
{
input: {
width: 1024,
height: 1024,
prompt: "a close up (analog style, dreamy portrait) (saturation:0.3), of a female, (gazing into the distance), posing on a cobble stone street in a scenic Italian rural landscape, windy, scenic sunset, perfect anatomy, (low contrast), analog style, dramatic lighting, atmospheric",
refiner: true,
denoising: 0.8,
seed_number: 12345,
guidance_scale: 7,
negative_prompt: "",
num_inference_steps: 50
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateSet the
REPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client
import replicateRun alexgenovese/sdxl-custom-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"alexgenovese/sdxl-custom-model:a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff",
input={
"width": 1024,
"height": 1024,
"prompt": "a close up (analog style, dreamy portrait) (saturation:0.3), of a female, (gazing into the distance), posing on a cobble stone street in a scenic Italian rural landscape, windy, scenic sunset, perfect anatomy, (low contrast), analog style, dramatic lighting, atmospheric",
"refiner": True,
"denoising": 0.8,
"seed_number": 12345,
"guidance_scale": 7,
"negative_prompt": "",
"num_inference_steps": 50
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run alexgenovese/sdxl-custom-model 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": "a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff",
"input": {
"width": 1024,
"height": 1024,
"prompt": "a close up (analog style, dreamy portrait) (saturation:0.3), of a female, (gazing into the distance), posing on a cobble stone street in a scenic Italian rural landscape, windy, scenic sunset, perfect anatomy, (low contrast), analog style, dramatic lighting, atmospheric",
"refiner": true,
"denoising": 0.8,
"seed_number": 12345,
"guidance_scale": 7,
"negative_prompt": "",
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Install Cog
brew install cogIf you don’t have Homebrew, there are other installation options available.
Pull and run alexgenovese/sdxl-custom-model using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/alexgenovese/sdxl-custom-model@sha256:a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff \
-i 'width=1024' \
-i 'height=1024' \
-i 'prompt="a close up (analog style, dreamy portrait) (saturation:0.3), of a female, (gazing into the distance), posing on a cobble stone street in a scenic Italian rural landscape, windy, scenic sunset, perfect anatomy, (low contrast), analog style, dramatic lighting, atmospheric"' \
-i 'refiner=true' \
-i 'denoising=0.8' \
-i 'seed_number=12345' \
-i 'guidance_scale=7' \
-i 'negative_prompt=""' \
-i 'num_inference_steps=50'To learn more, take a look at the Cog documentation.
Pull and run alexgenovese/sdxl-custom-model using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/alexgenovese/sdxl-custom-model@sha256:a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dffcurl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "a close up (analog style, dreamy portrait) (saturation:0.3), of a female, (gazing into the distance), posing on a cobble stone street in a scenic Italian rural landscape, windy, scenic sunset, perfect anatomy, (low contrast), analog style, dramatic lighting, atmospheric", "refiner": true, "denoising": 0.8, "seed_number": 12345, "guidance_scale": 7, "negative_prompt": "", "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Add a payment method to run this model.
Each run costs approximately $0.067. Alternatively, try out our featured models for free.
Sign in with GitHub
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terms of service and privacy policy
Output
{
"completed_at": "2023-11-19T12:22:34.929686Z",
"created_at": "2023-11-19T12:21:53.390554Z",
"data_removed": false,
"error": null,
"id": "3uwthblbvftpx6prpq4cjsczvy",
"input": {
"width": 1024,
"height": 1024,
"prompt": "a close up (analog style, dreamy portrait) (saturation:0.3), of a female, (gazing into the distance), posing on a cobble stone street in a scenic Italian rural landscape, windy, scenic sunset, perfect anatomy, (low contrast), analog style, dramatic lighting, atmospheric",
"refiner": true,
"denoising": 0.8,
"seed_number": 12345,
"guidance_scale": 7,
"negative_prompt": "",
"num_inference_steps": 50
},
"logs": "Starting fp16 torch.float32 cuda\nThe current API is supported for operating with a single LoRA file. You are trying to load and fuse more than one LoRA which is not well-supported.\nFused all loras in UNet\nApplied correction to prompts positive a close up (analog style, dreamy portrait)1.10 (saturation)0.30, of a female, (gazing into the distance)1.10, posing on a cobble stone street in a scenic Italian rural landscape, windy, scenic sunset, perfect anatomy, (low contrast)1.10, analog style, dramatic lighting, atmospheric, detailed eyes, (masterpiece,best quality,ultra_detailed,highres,absurdres)1.20, 4k, professional, intricate details even to the smallest particle, extreme detail of the environment, sharp portrait, well lit, (ultra realistic, realistic)1.90, beautiful shadows, bright, photo quality, masterpiece, 8k, ultra-detailed, highly detailed, sharp focus, award winning, octane render unreal engine, volumetrics dtx, high definition, bokeh, (fashion model)1.50, (realistic, photorealistic)2.00, (fashion-forward)1.30\nApplied correction to negative prompts ,(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art)1.40, (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name)1.20, (blur, blurry, grainy)1.10, morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur)1.30, (3D ,3D Game, 3D Game Scene, 3D Character)1.10, (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities)1.30, peopleneg, unaestheticXL_Jug6\nApplied optimization\nCreated compel for prompts\nStarting inference...\ntimestep: 951 max: 4.01 min: -4.31 mean: -0.02\n 0%| | 0/40 [00:00<?, ?it/s]\ntimestep: 932 max: 4.01 min: -4.32 mean: -0.02\n 2%|▎ | 1/40 [00:00<00:29, 1.31it/s]\ntimestep: 913 max: 4.01 min: -4.32 mean: -0.03\n 5%|▌ | 2/40 [00:01<00:29, 1.31it/s]\ntimestep: 894 max: 3.98 min: -4.33 mean: -0.03\n 8%|▊ | 3/40 [00:02<00:28, 1.31it/s]\ntimestep: 875 max: 3.98 min: -4.34 mean: -0.03\n 10%|█ | 4/40 [00:03<00:27, 1.31it/s]\ntimestep: 856 max: 3.95 min: -4.34 mean: -0.04\n 12%|█▎ | 5/40 [00:03<00:26, 1.31it/s]\ntimestep: 837 max: 3.94 min: -4.34 mean: -0.04\n 15%|█▌ | 6/40 [00:04<00:26, 1.31it/s]\ntimestep: 818 max: 3.92 min: -4.33 mean: -0.05\n 18%|█▊ | 7/40 [00:05<00:25, 1.31it/s]\ntimestep: 799 max: 3.9 min: -4.33 mean: -0.05\n 20%|██ | 8/40 [00:06<00:24, 1.30it/s]\ntimestep: 780 max: 3.89 min: -4.32 mean: -0.05\n 22%|██▎ | 9/40 [00:06<00:23, 1.31it/s]\ntimestep: 761 max: 3.88 min: -4.32 mean: -0.06\n 25%|██▌ | 10/40 [00:07<00:22, 1.31it/s]\ntimestep: 742 max: 3.87 min: -4.31 mean: -0.06\n 28%|██▊ | 11/40 [00:08<00:22, 1.31it/s]\ntimestep: 723 max: 3.86 min: -4.3 mean: -0.07\n 30%|███ | 12/40 [00:09<00:21, 1.31it/s]\ntimestep: 704 max: 3.84 min: -4.29 mean: -0.07\n 32%|███▎ | 13/40 [00:09<00:20, 1.31it/s]\ntimestep: 685 max: 3.82 min: -4.28 mean: -0.08\n 35%|███▌ | 14/40 [00:10<00:19, 1.31it/s]\ntimestep: 666 max: 3.8 min: -4.27 mean: -0.08\n 38%|███▊ | 15/40 [00:11<00:19, 1.31it/s]\ntimestep: 647 max: 3.78 min: -4.25 mean: -0.09\n 40%|████ | 16/40 [00:12<00:18, 1.31it/s]\ntimestep: 628 max: 3.75 min: -4.23 mean: -0.09\n 42%|████▎ | 17/40 [00:13<00:17, 1.31it/s]\ntimestep: 609 max: 3.73 min: -4.21 mean: -0.1\n 45%|████▌ | 18/40 [00:13<00:16, 1.31it/s]\ntimestep: 590 max: 3.7 min: -4.19 mean: -0.11\n 48%|████▊ | 19/40 [00:14<00:16, 1.31it/s]\ntimestep: 571 max: 3.68 min: -4.16 mean: -0.11\n 50%|█████ | 20/40 [00:15<00:15, 1.31it/s]\ntimestep: 552 max: 3.65 min: -4.14 mean: -0.11\n 52%|█████▎ | 21/40 [00:16<00:14, 1.31it/s]\ntimestep: 533 max: 3.62 min: -4.11 mean: -0.12\n 55%|█████▌ | 22/40 [00:16<00:13, 1.31it/s]\ntimestep: 514 max: 3.58 min: -4.1 mean: -0.12\n 57%|█████▊ | 23/40 [00:17<00:13, 1.31it/s]\ntimestep: 495 max: 3.55 min: -4.09 mean: -0.13\n 60%|██████ | 24/40 [00:18<00:12, 1.31it/s]\ntimestep: 476 max: 3.51 min: -4.08 mean: -0.13\n 62%|██████▎ | 25/40 [00:19<00:11, 1.31it/s]\ntimestep: 457 max: 3.46 min: -4.07 mean: -0.14\n 65%|██████▌ | 26/40 [00:19<00:10, 1.31it/s]\ntimestep: 438 max: 3.41 min: -4.06 mean: -0.14\n 68%|██████▊ | 27/40 [00:20<00:09, 1.31it/s]\ntimestep: 419 max: 3.36 min: -4.04 mean: -0.14\n 70%|███████ | 28/40 [00:21<00:09, 1.31it/s]\ntimestep: 400 max: 3.31 min: -4.02 mean: -0.15\n 72%|███████▎ | 29/40 [00:22<00:08, 1.31it/s]\ntimestep: 381 max: 3.31 min: -4.0 mean: -0.15\n 75%|███████▌ | 30/40 [00:22<00:07, 1.31it/s]\ntimestep: 362 max: 3.31 min: -3.97 mean: -0.15\n 78%|███████▊ | 31/40 [00:23<00:06, 1.30it/s]\ntimestep: 343 max: 3.31 min: -3.94 mean: -0.16\n 80%|████████ | 32/40 [00:24<00:06, 1.31it/s]\ntimestep: 324 max: 3.3 min: -3.91 mean: -0.16\n 82%|████████▎ | 33/40 [00:25<00:05, 1.31it/s]\ntimestep: 305 max: 3.29 min: -3.87 mean: -0.16\n 85%|████████▌ | 34/40 [00:26<00:04, 1.31it/s]\ntimestep: 286 max: 3.27 min: -3.84 mean: -0.17\n 88%|████████▊ | 35/40 [00:26<00:03, 1.31it/s]\ntimestep: 267 max: 3.26 min: -3.8 mean: -0.17\n 90%|█████████ | 36/40 [00:27<00:03, 1.31it/s]\ntimestep: 248 max: 3.24 min: -3.76 mean: -0.17\n 92%|█████████▎| 37/40 [00:28<00:02, 1.31it/s]\ntimestep: 229 max: 3.22 min: -3.71 mean: -0.17\n 95%|█████████▌| 38/40 [00:29<00:01, 1.31it/s]\ntimestep: 210 max: 3.2 min: -3.67 mean: -0.17\n 98%|█████████▊| 39/40 [00:29<00:00, 1.31it/s]\n100%|██████████| 40/40 [00:30<00:00, 1.31it/s]\n100%|██████████| 40/40 [00:30<00:00, 1.31it/s]\ntimestep: 181 max: 3.12 min: -3.53 mean: -0.18\n 0%| | 0/10 [00:00<?, ?it/s]\ntimestep: 161 max: 3.04 min: -3.41 mean: -0.18\n 10%|█ | 1/10 [00:00<00:05, 1.59it/s]\ntimestep: 141 max: 2.96 min: -3.28 mean: -0.18\n 20%|██ | 2/10 [00:01<00:05, 1.59it/s]\ntimestep: 121 max: 2.88 min: -3.16 mean:-0.18\n 30%|███ | 3/10 [00:01<00:04, 1.59it/s]\ntimestep: 101 max: 2.8 min: -3.05 mean: -0.18\n 40%|████ | 4/10 [00:02<00:03, 1.59it/s]\ntimestep: 81 max: 2.72 min: -2.93 mean:-0.18\n 50%|█████ | 5/10 [00:03<00:03, 1.59it/s]\ntimestep: 61 max: 2.64 min: -2.8 mean: -0.18\n 60%|██████ | 6/10 [00:03<00:02, 1.59it/s]\ntimestep: 41 max: 2.54 min: -2.66mean: -0.18\n 70%|███████ | 7/10 [00:04<00:01, 1.59it/s]\ntimestep: 21 max: 2.39 min: -2.45 mean: -0.18\n 80%|████████ | 8/10 [00:05<00:01, 1.59it/s]\ntimestep: 1 max: 2.35 min: -2.4 mean: -0.18\n 90%|█████████ | 9/10 [00:05<00:00, 1.59it/s]\n100%|██████████| 10/10 [00:06<00:00, 1.59it/s]\n100%|██████████| 10/10 [00:06<00:00, 1.59it/s]\nInference took: 41.16629600524902 30749",
"metrics": {
"predict_time": 41.525267,
"total_time": 41.539132
},
"output": "https://replicate.delivery/pbxt/IlwnbJH6BM5OJBpi7SPDJZqNVTTbtzwdGuq9rrk1qJmCwe8IA/image-30749-40.513755798339844.png",
"started_at": "2023-11-19T12:21:53.404419Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/3uwthblbvftpx6prpq4cjsczvy",
"cancel": "https://api.replicate.com/v1/predictions/3uwthblbvftpx6prpq4cjsczvy/cancel"
},
"version": "a08504bd6b123bb993f648c6361041a3cc3f721a24ab6a1619b10f03dd8c0dff"
}Generated in
Starting fp16 torch.float32 cuda
The current API is supported for operating with a single LoRA file. You are trying to load and fuse more than one LoRA which is not well-supported.
Fused all loras in UNet
Applied correction to prompts positive a close up (analog style, dreamy portrait)1.10 (saturation)0.30, of a female, (gazing into the distance)1.10, posing on a cobble stone street in a scenic Italian rural landscape, windy, scenic sunset, perfect anatomy, (low contrast)1.10, analog style, dramatic lighting, atmospheric, detailed eyes, (masterpiece,best quality,ultra_detailed,highres,absurdres)1.20, 4k, professional, intricate details even to the smallest particle, extreme detail of the environment, sharp portrait, well lit, (ultra realistic, realistic)1.90, beautiful shadows, bright, photo quality, masterpiece, 8k, ultra-detailed, highly detailed, sharp focus, award winning, octane render unreal engine, volumetrics dtx, high definition, bokeh, (fashion model)1.50, (realistic, photorealistic)2.00, (fashion-forward)1.30
Applied correction to negative prompts ,(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art)1.40, (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name)1.20, (blur, blurry, grainy)1.10, morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur)1.30, (3D ,3D Game, 3D Game Scene, 3D Character)1.10, (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities)1.30, peopleneg, unaestheticXL_Jug6
Applied optimization
Created compel for prompts
Starting inference...
timestep: 951 max: 4.01 min: -4.31 mean: -0.02
0%| | 0/40 [00:00<?, ?it/s]
timestep: 932 max: 4.01 min: -4.32 mean: -0.02
2%|▎ | 1/40 [00:00<00:29, 1.31it/s]
timestep: 913 max: 4.01 min: -4.32 mean: -0.03
5%|▌ | 2/40 [00:01<00:29, 1.31it/s]
timestep: 894 max: 3.98 min: -4.33 mean: -0.03
8%|▊ | 3/40 [00:02<00:28, 1.31it/s]
timestep: 875 max: 3.98 min: -4.34 mean: -0.03
10%|█ | 4/40 [00:03<00:27, 1.31it/s]
timestep: 856 max: 3.95 min: -4.34 mean: -0.04
12%|█▎ | 5/40 [00:03<00:26, 1.31it/s]
timestep: 837 max: 3.94 min: -4.34 mean: -0.04
15%|█▌ | 6/40 [00:04<00:26, 1.31it/s]
timestep: 818 max: 3.92 min: -4.33 mean: -0.05
18%|█▊ | 7/40 [00:05<00:25, 1.31it/s]
timestep: 799 max: 3.9 min: -4.33 mean: -0.05
20%|██ | 8/40 [00:06<00:24, 1.30it/s]
timestep: 780 max: 3.89 min: -4.32 mean: -0.05
22%|██▎ | 9/40 [00:06<00:23, 1.31it/s]
timestep: 761 max: 3.88 min: -4.32 mean: -0.06
25%|██▌ | 10/40 [00:07<00:22, 1.31it/s]
timestep: 742 max: 3.87 min: -4.31 mean: -0.06
28%|██▊ | 11/40 [00:08<00:22, 1.31it/s]
timestep: 723 max: 3.86 min: -4.3 mean: -0.07
30%|███ | 12/40 [00:09<00:21, 1.31it/s]
timestep: 704 max: 3.84 min: -4.29 mean: -0.07
32%|███▎ | 13/40 [00:09<00:20, 1.31it/s]
timestep: 685 max: 3.82 min: -4.28 mean: -0.08
35%|███▌ | 14/40 [00:10<00:19, 1.31it/s]
timestep: 666 max: 3.8 min: -4.27 mean: -0.08
38%|███▊ | 15/40 [00:11<00:19, 1.31it/s]
timestep: 647 max: 3.78 min: -4.25 mean: -0.09
40%|████ | 16/40 [00:12<00:18, 1.31it/s]
timestep: 628 max: 3.75 min: -4.23 mean: -0.09
42%|████▎ | 17/40 [00:13<00:17, 1.31it/s]
timestep: 609 max: 3.73 min: -4.21 mean: -0.1
45%|████▌ | 18/40 [00:13<00:16, 1.31it/s]
timestep: 590 max: 3.7 min: -4.19 mean: -0.11
48%|████▊ | 19/40 [00:14<00:16, 1.31it/s]
timestep: 571 max: 3.68 min: -4.16 mean: -0.11
50%|█████ | 20/40 [00:15<00:15, 1.31it/s]
timestep: 552 max: 3.65 min: -4.14 mean: -0.11
52%|█████▎ | 21/40 [00:16<00:14, 1.31it/s]
timestep: 533 max: 3.62 min: -4.11 mean: -0.12
55%|█████▌ | 22/40 [00:16<00:13, 1.31it/s]
timestep: 514 max: 3.58 min: -4.1 mean: -0.12
57%|█████▊ | 23/40 [00:17<00:13, 1.31it/s]
timestep: 495 max: 3.55 min: -4.09 mean: -0.13
60%|██████ | 24/40 [00:18<00:12, 1.31it/s]
timestep: 476 max: 3.51 min: -4.08 mean: -0.13
62%|██████▎ | 25/40 [00:19<00:11, 1.31it/s]
timestep: 457 max: 3.46 min: -4.07 mean: -0.14
65%|██████▌ | 26/40 [00:19<00:10, 1.31it/s]
timestep: 438 max: 3.41 min: -4.06 mean: -0.14
68%|██████▊ | 27/40 [00:20<00:09, 1.31it/s]
timestep: 419 max: 3.36 min: -4.04 mean: -0.14
70%|███████ | 28/40 [00:21<00:09, 1.31it/s]
timestep: 400 max: 3.31 min: -4.02 mean: -0.15
72%|███████▎ | 29/40 [00:22<00:08, 1.31it/s]
timestep: 381 max: 3.31 min: -4.0 mean: -0.15
75%|███████▌ | 30/40 [00:22<00:07, 1.31it/s]
timestep: 362 max: 3.31 min: -3.97 mean: -0.15
78%|███████▊ | 31/40 [00:23<00:06, 1.30it/s]
timestep: 343 max: 3.31 min: -3.94 mean: -0.16
80%|████████ | 32/40 [00:24<00:06, 1.31it/s]
timestep: 324 max: 3.3 min: -3.91 mean: -0.16
82%|████████▎ | 33/40 [00:25<00:05, 1.31it/s]
timestep: 305 max: 3.29 min: -3.87 mean: -0.16
85%|████████▌ | 34/40 [00:26<00:04, 1.31it/s]
timestep: 286 max: 3.27 min: -3.84 mean: -0.17
88%|████████▊ | 35/40 [00:26<00:03, 1.31it/s]
timestep: 267 max: 3.26 min: -3.8 mean: -0.17
90%|█████████ | 36/40 [00:27<00:03, 1.31it/s]
timestep: 248 max: 3.24 min: -3.76 mean: -0.17
92%|█████████▎| 37/40 [00:28<00:02, 1.31it/s]
timestep: 229 max: 3.22 min: -3.71 mean: -0.17
95%|█████████▌| 38/40 [00:29<00:01, 1.31it/s]
timestep: 210 max: 3.2 min: -3.67 mean: -0.17
98%|█████████▊| 39/40 [00:29<00:00, 1.31it/s]
100%|██████████| 40/40 [00:30<00:00, 1.31it/s]
100%|██████████| 40/40 [00:30<00:00, 1.31it/s]
timestep: 181 max: 3.12 min: -3.53 mean: -0.18
0%| | 0/10 [00:00<?, ?it/s]
timestep: 161 max: 3.04 min: -3.41 mean: -0.18
10%|█ | 1/10 [00:00<00:05, 1.59it/s]
timestep: 141 max: 2.96 min: -3.28 mean: -0.18
20%|██ | 2/10 [00:01<00:05, 1.59it/s]
timestep: 121 max: 2.88 min: -3.16 mean:-0.18
30%|███ | 3/10 [00:01<00:04, 1.59it/s]
timestep: 101 max: 2.8 min: -3.05 mean: -0.18
40%|████ | 4/10 [00:02<00:03, 1.59it/s]
timestep: 81 max: 2.72 min: -2.93 mean:-0.18
50%|█████ | 5/10 [00:03<00:03, 1.59it/s]
timestep: 61 max: 2.64 min: -2.8 mean: -0.18
60%|██████ | 6/10 [00:03<00:02, 1.59it/s]
timestep: 41 max: 2.54 min: -2.66mean: -0.18
70%|███████ | 7/10 [00:04<00:01, 1.59it/s]
timestep: 21 max: 2.39 min: -2.45 mean: -0.18
80%|████████ | 8/10 [00:05<00:01, 1.59it/s]
timestep: 1 max: 2.35 min: -2.4 mean: -0.18
90%|█████████ | 9/10 [00:05<00:00, 1.59it/s]
100%|██████████| 10/10 [00:06<00:00, 1.59it/s]
100%|██████████| 10/10 [00:06<00:00, 1.59it/s]
Inference took: 41.16629600524902 30749