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 generation_config.json from Dibachain/Diba-Embed: direct link, hf CLI and curl.
- Browser
- Download file 117 Bytes
-
https://huggingface.co/Dibachain/Diba-Embed/resolve/main/generation_config.json
- Command line
-
hf download hf://Dibachain/Diba-Embed/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/Dibachain/Diba-Embed/resolve/main/generation_config.json
117 Bytes
| { | |
| "bos_token_id": 151643, | |
| "eos_token_id": 151643, | |
| "max_new_tokens": 2048, | |
| "transformers_version": "4.51.3" | |
| } | |