Feature Extraction
Transformers
PyTorch
ONNX
Safetensors
sentence-transformers
sentence-similarity
mteb
custom_code
Eval Results (legacy)
Eval Results
🇪🇺 Region: EU
Instructions to use jinaai/jina-embeddings-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinaai/jina-embeddings-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jinaai/jina-embeddings-v3", trust_remote_code=True)# Load model directly from transformers import AutoModelForMultimodalLM model = AutoModelForMultimodalLM.from_pretrained("jinaai/jina-embeddings-v3", trust_remote_code=True, dtype="auto") - sentence-transformers
How to use jinaai/jina-embeddings-v3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jinaai/jina-embeddings-v3", 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
Where vocab save ?
#107
by batman9x - opened
Jinaai-embedding-v3 not save vocab ? Don't see vocab
The vocab of the model is stored in the tokenizer.json file, which is included in the repository. However, since this file is managed with Git LFS, you need to ensure that Git LFS is installed and set up correctly to access the actual content of the file.