Sentence Similarity
TensorBoard
Safetensors
sentence-transformers
PyLate
bert
ColBERT
feature-extraction
Generated from Trainer
dataset_size:983844
loss:Contrastive
Eval Results (legacy)
text-embeddings-inference
Instructions to use yosefw/colbert-bert-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yosefw/colbert-bert-mini 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="yosefw/colbert-bert-mini") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c49aadc1f86c8e58809791fa6da1024e3b3a5aeb1a6f4f5ecea14d145e51a37e
- Size of remote file:
- 5.62 kB
- SHA256:
- 9892ac0c424444321dab53089f7e135bfab3511c1a982fd2fea616bcb359f3c6
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