Feature Extraction
Transformers
Safetensors
English
lessvit
hyperspectral
remote-sensing
geospatial
vision-transformer
custom_code
Instructions to use GFM-Bench/LESSViT-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GFM-Bench/LESSViT-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="GFM-Bench/LESSViT-Base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GFM-Bench/LESSViT-Base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download requirements.txt from GFM-Bench/LESSViT-Base: direct link, hf CLI and curl.
- Browser
- Download file 126 Bytes
-
https://huggingface.co/GFM-Bench/LESSViT-Base/resolve/main/requirements.txt
- Command line
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hf download hf://GFM-Bench/LESSViT-Base/requirements.txt
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curl -L -o requirements.txt https://huggingface.co/GFM-Bench/LESSViT-Base/resolve/main/requirements.txt
126 Bytes
| torch==2.7.1 | |
| torchvision==0.22.1 | |
| transformers==4.53.3 | |
| huggingface-hub==0.34.4 | |
| timm==1.0.18 | |
| numpy==2.2.6 | |
| safetensors>=0.4.3,<1 | |