Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use bachngo/intf-e5-small-5t with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bachngo/intf-e5-small-5t with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bachngo/intf-e5-small-5t") 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 tokenizer.json from bachngo/intf-e5-small-5t: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/bachngo/intf-e5-small-5t/resolve/main/tokenizer.json
- Command line
-
hf download hf://bachngo/intf-e5-small-5t/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bachngo/intf-e5-small-5t/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- ba683d59c18486567514fdfee65d1a8f8a4a99c525dbf1c21693d0d9188082f4
- Size of remote file:
- 17.1 MB
- SHA256:
- 45b6ee00bc5023ac454b82c372ebe14b27866fa471b6dbb0d24e09b12909a1f4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.