sentence-transformers
ONNX
Safetensors
English
bert
ColBERT
multi-vector
RAGatouille
passage-retrieval
Instructions to use answerdotai/answerai-colbert-small-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use answerdotai/answerai-colbert-small-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("answerdotai/answerai-colbert-small-v1") 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
minor typo (#10)
Browse files- minor typo (715cb9ff57295a1f320ccf6a6e3c42a5f1a438e6)
Co-authored-by: Nicholas Broad <nbroad@users.noreply.huggingface.co>
README.md
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@@ -54,7 +54,7 @@ RAG = RAGPretrainedModel.from_pretrained("answerdotai/answerai-colbert-small-v1"
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docs = ['Hayao Miyazaki is a Japanese director, born on [...]', 'Walt Disney is an American author, director and [...]', ...]
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RAG.index(
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query = 'Who directed spirited away?'
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results = RAG.search(query)
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docs = ['Hayao Miyazaki is a Japanese director, born on [...]', 'Walt Disney is an American author, director and [...]', ...]
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RAG.index(docs, index_name="ghibli")
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query = 'Who directed spirited away?'
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results = RAG.search(query)
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