Sentence Similarity
Transformers
Safetensors
Vietnamese
xlm-roberta
embedding
text-embeddings-inference
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:
# Load model directly from transformers import AutoTokenizer, ViDense tokenizer = AutoTokenizer.from_pretrained("namdp-ptit/ViDense") model = ViDense.from_pretrained("namdp-ptit/ViDense") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8015d3ca1046a0eaf1557d3d4e19edc9db48ef4c9f1a435cfc5dbefa2b346f61
- Size of remote file:
- 1.34 kB
- SHA256:
- b9d8c0775c00cf12081ab13fe825961ad83c294b9c7b8efd4b431b1799ea5c01
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