Sentence Similarity
sentence-transformers
Safetensors
multilingual
bert
narrative-similarity
cross-lingual-retrieval
tip-of-the-tongue
text-embeddings-inference
Instructions to use Jgmorenof/plots-labse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Jgmorenof/plots-labse with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Jgmorenof/plots-labse") 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 Jgmorenof/plots-labse: direct link, hf CLI and curl.
- Browser
- Download file 13.6 MB
-
https://huggingface.co/Jgmorenof/plots-labse/resolve/main/tokenizer.json
- Command line
-
hf download hf://Jgmorenof/plots-labse/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Jgmorenof/plots-labse/resolve/main/tokenizer.json
13.6 MB
- Xet hash:
- 5d1111676eb55e5661f171e7af9a80a20ceb9872b98843b0186041f2980f15a6
- Size of remote file:
- 13.6 MB
- SHA256:
- e160a07b3b76c68cd214747a559d36e04109c9fc522ccfce79548098ce85da2a
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