Feature Extraction
sentence-transformers
Safetensors
gemma3_text
retrieval
devdata-search
text-embeddings-inference
Instructions to use ai4data/devdata-search-harrier-270m-cmnrl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ai4data/devdata-search-harrier-270m-cmnrl with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ai4data/devdata-search-harrier-270m-cmnrl") 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
- Xet hash:
- 9abe59178c1065c84a08fda4b8faf2fb03f7abcc6e27ddcb891e461c54ea3a53
- Size of remote file:
- 33.4 MB
- SHA256:
- d6c4c6c7ecda463434a6fafacc071da6de4a1c644d58d2c14de03520ecb8ff32
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.