Feature Extraction
sentence-transformers
Safetensors
English
colqwen2
multi-vector
colbert
late-interaction
Generated from Trainer
dataset_size:3475
loss:MultiVectorMultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use tomaarsen/multivector-colqwen2-v1.0-hf-docqa-energy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tomaarsen/multivector-colqwen2-v1.0-hf-docqa-energy with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tomaarsen/multivector-colqwen2-v1.0-hf-docqa-energy") 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:
- 3fe95edf72f39db87456c28023d40ea52640a115a1a58f662bbc3b1cc8bdc309
- Size of remote file:
- 11.4 MB
- SHA256:
- bac488975eccb4e1cbcf65979b644ac7e0ba71721f1ea36a52bd4b5fb81497b3
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