Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
text-embeddings-inference
4-bit precision
bitsandbytes
Instructions to use FareedKhan/mx_bai_test_q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use FareedKhan/mx_bai_test_q4 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("FareedKhan/mx_bai_test_q4") 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 FareedKhan/mx_bai_test_q4: direct link, hf CLI and curl.
- Browser
- Download file 12.3 MB
-
https://huggingface.co/FareedKhan/mx_bai_test_q4/resolve/main/tokenizer.json
- Command line
-
hf download hf://FareedKhan/mx_bai_test_q4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/FareedKhan/mx_bai_test_q4/resolve/main/tokenizer.json
12.3 MB
- Xet hash:
- 130e65eacd392921a327df38216c0295960f9c3a377ba5410e649b4f5bcd7432
- Size of remote file:
- 12.3 MB
- SHA256:
- b319c37e4f1e5f8f1c8dba7e1bc7b1a424184365d7f982ada0f18ab60c514c07
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