Feature Extraction
sentence-transformers
Safetensors
modernbert
multi-vector
colbert
late-interaction
Generated from Trainer
dataset_size:1000000
loss:CachedMultiVectorMultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use multi-vector-encoder/mLateOn-medical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use multi-vector-encoder/mLateOn-medical with sentence-transformers:
from sentence_transformers import MultiVectorEncoder model = MultiVectorEncoder("multi-vector-encoder/mLateOn-medical") queries = ["Which planet is known as the Red Planet?"] documents = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) - Notebooks
- Google Colab
- Kaggle
Download modules.json from multi-vector-encoder/mLateOn-medical: direct link, hf CLI and curl.
- Browser
- Download file 811 Bytes
-
https://huggingface.co/multi-vector-encoder/mLateOn-medical/resolve/main/modules.json
- Command line
-
hf download hf://multi-vector-encoder/mLateOn-medical/modules.json
-
curl -L -o modules.json https://huggingface.co/multi-vector-encoder/mLateOn-medical/resolve/main/modules.json
811 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.base.modules.transformer.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Dense", | |
| "type": "sentence_transformers.base.modules.dense.Dense" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Dense", | |
| "type": "sentence_transformers.base.modules.dense.Dense" | |
| }, | |
| { | |
| "idx": 3, | |
| "name": "3", | |
| "path": "3_Dense", | |
| "type": "sentence_transformers.base.modules.dense.Dense" | |
| }, | |
| { | |
| "idx": 4, | |
| "name": "4", | |
| "path": "4_MultiVectorMask", | |
| "type": "sentence_transformers.multi_vector_encoder.modules.multi_vector_mask.MultiVectorMask" | |
| }, | |
| { | |
| "idx": 5, | |
| "name": "5", | |
| "path": "5_Normalize", | |
| "type": "sentence_transformers.base.modules.normalize.Normalize" | |
| } | |
| ] |