Sentence Similarity
sentence-transformers
Safetensors
GGUF
Persian
English
diba_embed
feature-extraction
text-embeddings
persian
farsi
iran
retrieval
rag
semantic-search
multilingual
dibachain
llama.cpp
custom_code
Instructions to use Dibachain/Diba-Embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Dibachain/Diba-Embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Dibachain/Diba-Embed", trust_remote_code=True) 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 2_Normalize/config.json from Dibachain/Diba-Embed: direct link, hf CLI and curl.
- Browser
- Download file 2 Bytes
-
https://huggingface.co/Dibachain/Diba-Embed/resolve/main/2_Normalize/config.json
- Command line
-
hf download hf://Dibachain/Diba-Embed/2_Normalize/config.json
-
curl -L -o config.json https://huggingface.co/Dibachain/Diba-Embed/resolve/main/2_Normalize/config.json
2 Bytes
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