Instructions to use Wjjjh/lingbot-va-libero-goal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wjjjh/lingbot-va-libero-goal with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wjjjh/lingbot-va-libero-goal", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download norm_stats.json from Wjjjh/lingbot-va-libero-goal: direct link, hf CLI and curl.
- Browser
- Download file 477 Bytes
-
https://huggingface.co/Wjjjh/lingbot-va-libero-goal/resolve/main/norm_stats.json
- Command line
-
hf download hf://Wjjjh/lingbot-va-libero-goal/norm_stats.json
-
curl -L -o norm_stats.json https://huggingface.co/Wjjjh/lingbot-va-libero-goal/resolve/main/norm_stats.json
477 Bytes
| { | |
| "suite": "libero_goal", | |
| "action_norm_method": "quantiles", | |
| "used_action_channel_ids": [ | |
| 0, | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 5, | |
| 6 | |
| ], | |
| "action_snr_shift": 0.05, | |
| "q01": [ | |
| -0.8973214030265808, | |
| -0.7473214268684387, | |
| -0.9375, | |
| -0.15214285254478455, | |
| -0.16256785675883295, | |
| -0.14142857491970062, | |
| -1.0 | |
| ], | |
| "q99": [ | |
| 0.9375, | |
| 0.9133928418159485, | |
| 0.9375, | |
| 0.21214285492897034, | |
| 0.2582142949104309, | |
| 0.375, | |
| 1.0 | |
| ] | |
| } | |