Sentence Similarity
Safetensors
GGUF
sentence-transformers
multilingual
llama.cpp
eurobert
embedding
llama-cpp
jina-embeddings-v5
feature-extraction
mteb
vllm
custom_code
Instructions to use noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi", 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 config_sentence_transformers.json from noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi: direct link, hf CLI and curl.
- Browser
- Download file 299 Bytes
-
https://huggingface.co/noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/noname002/jina-embeddings-v5-text-nano-retrieval-mc4-vi/resolve/main/config_sentence_transformers.json
299 Bytes
| { | |
| "__version__": { | |
| "pytorch": "2.9.1+cu128", | |
| "sentence_transformers": "5.4.1", | |
| "transformers": "5.5.4" | |
| }, | |
| "default_prompt_name": null, | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "document": "Document: ", | |
| "query": "Query: " | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |