Feature Extraction
sentence-transformers
Safetensors
slideon
sparse
sentence-similarity
custom-code
multilingual
code-search
sparse-retrieval
matryoshka
custom_code
🇪🇺 Region: EU
Instructions to use lightonai/mSlideOn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/mSlideOn with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lightonai/mSlideOn", trust_remote_code=True) 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] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from lightonai/mSlideOn: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/lightonai/mSlideOn/resolve/main/tokenizer.json
- Command line
-
hf download hf://lightonai/mSlideOn/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/lightonai/mSlideOn/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 53a4479c7ceaaaca701335375279aec5354f76298aa1fa7a07d824f9c9ceb7e1
- Size of remote file:
- 34.4 MB
- SHA256:
- 33b6ce1724e107a3298219a322b4c963fcfcb9c8661bd1f30189bdd0d36c4669
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