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
Community Contribution: Showcase Colab Notebook for jina-embeddings-v5-small
2
#21 opened 3 months ago
by
matifema
Can you help me to give code of finetuning the embedding model according to our own dataset
1
#20 opened 3 months ago
by
RohitUltimate
Installation Video and Testing - Step by Step
❤️ 1
#15 opened 5 months ago
by
fahdmirzac
v5 GGUF filenames don't have model name prefixes
#14 opened 5 months ago
by
rotemdan
No late chunking ability?
1
#9 opened 5 months ago
by
Tedvalson