Instructions to use metarank/all-MiniLM-L6-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use metarank/all-MiniLM-L6-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("metarank/all-MiniLM-L6-v2") 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 metarank/all-MiniLM-L6-v2: direct link, hf CLI and curl.
- Browser
- Download file 466 kB
-
https://huggingface.co/metarank/all-MiniLM-L6-v2/resolve/main/tokenizer.json
- Command line
-
hf download hf://metarank/all-MiniLM-L6-v2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/metarank/all-MiniLM-L6-v2/resolve/main/tokenizer.json
466 kB
- Xet hash:
- 5fa8ac83b995e3d9e9dad9810d2d1ea0a93faa73502bc59a1c80348a62e662bb
- Size of remote file:
- 466 kB
- SHA256:
- be50c3628f2bf5bb5e3a7f17b1f74611b2561a3a27eeab05e5aa30f411572037
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