Feature Extraction
Transformers
Safetensors
sentence-transformers
multilingual
jina_embeddings_v5
mteb
custom_code
🇪🇺 Region: EU
Instructions to use jinaai/jina-embeddings-v5-text-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinaai/jina-embeddings-v5-text-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jinaai/jina-embeddings-v5-text-small", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jinaai/jina-embeddings-v5-text-small", trust_remote_code=True, device_map="auto") - sentence-transformers
How to use jinaai/jina-embeddings-v5-text-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jinaai/jina-embeddings-v5-text-small", 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
| { | |
| "bos_token_id": 151643, | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "pad_token_id": 151643, | |
| "temperature": 0.6, | |
| "top_k": 20, | |
| "top_p": 0.95, | |
| "transformers_version": "4.51.0" | |
| } |