Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
mpnet
feature-extraction
Trained with AutoTrain
text-embeddings-inference
Instructions to use sidbrahim/narrativesAnalogues-MPNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sidbrahim/narrativesAnalogues-MPNet with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sidbrahim/narrativesAnalogues-MPNet") sentences = [ "search_query: i love autotrain", "search_query: huggingface auto train", "search_query: hugging face auto train", "search_query: i love autotrain" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download checkpoint-396/optimizer.pt from sidbrahim/narrativesAnalogues-MPNet: direct link, hf CLI and curl.
- Browser
- Download file 871 MB
-
https://huggingface.co/sidbrahim/narrativesAnalogues-MPNet/resolve/main/checkpoint-396/optimizer.pt
- Command line
-
hf download hf://sidbrahim/narrativesAnalogues-MPNet/checkpoint-396/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/sidbrahim/narrativesAnalogues-MPNet/resolve/main/checkpoint-396/optimizer.pt
871 MB
- Xet hash:
- 43b3caf867244cdd93be1bd0c1ac0afa70740d3ef169347330737b05385adf46
- Size of remote file:
- 871 MB
- SHA256:
- de49a5b8b7876c6c549e844e1b45f621f051494f3dd12c7a30ee5b8ad0df4dec
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