Sentence Similarity
sentence-transformers
Safetensors
English
esm
protein
esm2
contrastive-learning
protein-embeddings
biology
Instructions to use GrimSqueaker/ProtSent-V2-150M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use GrimSqueaker/ProtSent-V2-150M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GrimSqueaker/ProtSent-V2-150M") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "<cls>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "1": { | |
| "content": "<pad>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "2": { | |
| "content": "<eos>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "3": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "32": { | |
| "content": "<mask>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "backend": "custom", | |
| "bos_token": "<cls>", | |
| "cls_token": "<cls>", | |
| "eos_token": "<eos>", | |
| "is_local": true, | |
| "local_files_only": true, | |
| "mask_token": "<mask>", | |
| "model_max_length": 1026, | |
| "pad_token": "<pad>", | |
| "tokenizer_class": "EsmTokenizer", | |
| "unk_token": "<unk>" | |
| } |