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
File size: 335 Bytes
ffd2587 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"transformer_task": "retrieval",
"modality_config": {
"text": {
"method": "forward",
"method_output_name": "embeddings"
},
"image": {
"method": "forward",
"method_output_name": "embeddings"
}
},
"module_output_name": "token_embeddings"
} |