Instructions to use namdp-ptit/ViDense with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namdp-ptit/ViDense with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, ViDense tokenizer = AutoTokenizer.from_pretrained("namdp-ptit/ViDense") model = ViDense.from_pretrained("namdp-ptit/ViDense", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download colbert_linear.pt from namdp-ptit/ViDense: direct link, hf CLI and curl.
- Browser
- Download file 2.1 MB
-
https://huggingface.co/namdp-ptit/ViDense/resolve/main/colbert_linear.pt
- Command line
-
hf download hf://namdp-ptit/ViDense/colbert_linear.pt
-
curl -L -o colbert_linear.pt https://huggingface.co/namdp-ptit/ViDense/resolve/main/colbert_linear.pt
2.1 MB
- Xet hash:
- c79b3cde48a5e1e523cba383ecb3e377394ffcaa745bb14c1a94561b4adefdaf
- Size of remote file:
- 2.1 MB
- SHA256:
- 19bfbae397c2b7524158c919d0e9b19393c5639d098f0a66932c91ed8f5f9abb
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