Instructions to use Maunish/ext_sentbert-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maunish/ext_sentbert-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Maunish/ext_sentbert-5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Maunish/ext_sentbert-5") model = AutoModel.from_pretrained("Maunish/ext_sentbert-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Maunish/ext_sentbert-5: direct link, hf CLI and curl.
- Browser
- Download file 90.9 MB
-
https://huggingface.co/Maunish/ext_sentbert-5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Maunish/ext_sentbert-5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Maunish/ext_sentbert-5/resolve/main/pytorch_model.bin
90.9 MB
- Xet hash:
- 7068e59aa0f1ffc33882275db09671b6791c06a81ccc76199e23cef3dd1c7ecb
- Size of remote file:
- 90.9 MB
- SHA256:
- d0920039056fc7af8af1294a1070a3e46517ce30c1f9457b4331a769c908aa64
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