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 pytorch_model.bin from namdp-ptit/ViDense: direct link, hf CLI and curl.
- Browser
- Download file 2.27 GB
-
https://huggingface.co/namdp-ptit/ViDense/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://namdp-ptit/ViDense/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/namdp-ptit/ViDense/resolve/main/pytorch_model.bin
2.27 GB
- Xet hash:
- 61c2417ef33baa8496de69bd4394784d9b887a9027830afeac7e2ab8b4e1a6f1
- Size of remote file:
- 2.27 GB
- SHA256:
- b5e0ce3470abf5ef3831aa1bd5553b486803e83251590ab7ff35a117cf6aad38
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