Instructions to use HasinMDG/X-Sent-mdeberta-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HasinMDG/X-Sent-mdeberta-v4 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HasinMDG/X-Sent-mdeberta-v4") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - setfit
How to use HasinMDG/X-Sent-mdeberta-v4 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("HasinMDG/X-Sent-mdeberta-v4") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from HasinMDG/X-Sent-mdeberta-v4: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/HasinMDG/X-Sent-mdeberta-v4/resolve/main/tokenizer.json
- Command line
-
hf download hf://HasinMDG/X-Sent-mdeberta-v4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/HasinMDG/X-Sent-mdeberta-v4/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- c8ba5db76b8a3347d94e706ec8bfc82a381d515952c2bc6338d06ad806042dba
- Size of remote file:
- 16.3 MB
- SHA256:
- 63ce2c686f361e1153f8b0729f2dbeffc005c57009579e9d34ca1726f324b2a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.