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
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<|begin_of_text|>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|end_of_text|>", | |
| "is_local": true, | |
| "mask_token": "<|mask|>", | |
| "max_length": null, | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<|pad|>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "tokenizer_class": "TokenizersBackend" | |
| } | |