Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
Generated from Trainer
dataset_size:3396
loss:SoftmaxLoss
text-embeddings-inference
Instructions to use cafierom/smiles_embedding_gemma_FT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cafierom/smiles_embedding_gemma_FT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cafierom/smiles_embedding_gemma_FT") sentences = [ "C[C@H](CCCC(C)(C)O)[C@H]1CC[C@H]2[C@@H]3CC=C4C[C@@H](O)CC[C@]4(C)[C@H]3CC[C@]12C", "CC(C)n1c(CC[C@@H](O)C[C@@H](O)CC([O-])=O)c(c(c1C(=O)NCc1ccccn1)-c1ccccc1)-c1ccc(F)cc1", "Cc1cc(OCc2ccccc2)cc(C)c1\\C=C\\[C@@H]1C[C@@H](O)CC(=O)O1", "Cc1ccc(C2CC3CCC2C=C3)n1CC[C@@H]1C[C@@H](O)CC(=O)O1" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 867 Bytes
363e391 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | {
"backend": "tokenizers",
"boi_token": "<start_of_image>",
"bos_token": "<bos>",
"clean_up_tokenization_spaces": false,
"eoi_token": "<end_of_image>",
"eos_token": "<eos>",
"image_token": "<image_soft_token>",
"is_local": true,
"local_files_only": false,
"mask_token": "<mask>",
"max_length": 128,
"model_max_length": 128,
"model_specific_special_tokens": {
"boi_token": "<start_of_image>",
"eoi_token": "<end_of_image>",
"image_token": "<image_soft_token>"
},
"pad_to_multiple_of": null,
"pad_token": "<pad>",
"pad_token_type_id": 0,
"padding_side": "right",
"sp_model_kwargs": null,
"spaces_between_special_tokens": false,
"stride": 0,
"tokenizer_class": "GemmaTokenizer",
"truncation_side": "right",
"truncation_strategy": "longest_first",
"unk_token": "<unk>",
"use_default_system_prompt": false
}
|