Robotics
Transformers
Safetensors
bitvla
feature-extraction
vision-language-action
vla
1-bit
bitnet
custom_code
Instructions to use lxsy/bitvla-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lxsy/bitvla-bf16 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("lxsy/bitvla-bf16", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from lxsy/bitvla-bf16: direct link, hf CLI and curl.
- Browser
- Download file 393 Bytes
-
https://huggingface.co/lxsy/bitvla-bf16/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://lxsy/bitvla-bf16/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/lxsy/bitvla-bf16/resolve/main/preprocessor_config.json
393 Bytes
| { | |
| "do_convert_rgb": null, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "SiglipImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "LlavaProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| } | |
| } | |