Sentence Similarity
Safetensors
sentence-transformers
PyLate
lfm2
liquid
edge
ColBERT
feature-extraction
Eval Results (legacy)
Instructions to use LiquidAI/LFM2-ColBERT-350M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LiquidAI/LFM2-ColBERT-350M with sentence-transformers:
from pylate import models queries = [ "Which planet is known as the Red Planet?", "What is the largest planet in our solar system?", ] documents = [ ["Mars is the Red Planet.", "Venus is Earth's twin."], ["Jupiter is the largest planet.", "Saturn has rings."], ] model = models.ColBERT(model_name_or_path="LiquidAI/LFM2-ColBERT-350M") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
Update README.md
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by zwischenraum - opened
README.md
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@@ -913,7 +913,7 @@ retriever = retrieve.ColBERT(index=index)
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queries_embeddings = model.encode(
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["query for document 3", "query for document 1"],
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batch_size=32,
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is_query=True, # # Ensure that it is set to
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show_progress_bar=True,
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)
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queries_embeddings = model.encode(
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["query for document 3", "query for document 1"],
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batch_size=32,
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is_query=True, # # Ensure that it is set to True to indicate that these are queries
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show_progress_bar=True,
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)
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