Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
English
bert
text-embeddings-inference
Instructions to use guyhadad01/EncodeRec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use guyhadad01/EncodeRec with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("guyhadad01/EncodeRec") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from guyhadad01/EncodeRec: direct link, hf CLI and curl.
- Browser
- Download file 181 MB
-
https://huggingface.co/guyhadad01/EncodeRec/resolve/00a697d06d028a79ee4cf4da3434a0eea24d5b80/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://guyhadad01/EncodeRec@00a697d06d028a79ee4cf4da3434a0eea24d5b80/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/guyhadad01/EncodeRec/resolve/00a697d06d028a79ee4cf4da3434a0eea24d5b80/last-checkpoint/optimizer.pt
181 MB
- Xet hash:
- f779abf73447b468416d6c395a18ffb1f09a3cfe66c994107d34f5c63f127667
- Size of remote file:
- 181 MB
- SHA256:
- 12655e53ef206d715a3442591f73e41f1140d40b95f274af76ba0a35f493edb8
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