Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
dense
Generated from Trainer
dataset_size:84996
loss:SoftmaxLoss
text-embeddings-inference
Instructions to use cafierom/smiles_embedding_gemma_FT_full 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_full with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cafierom/smiles_embedding_gemma_FT_full") sentences = [ "O[C@H](C[C@H](O)\\C=C\\c1c2CCCC(Cc3ccc(Cl)cc3)c2nn1-c1ccc(F)cc1)CC([O-])=O", "CC(C)c1sc(c(c1\\C=C\\[C@@H](O)C[C@@H](O)CC([O-])=O)-c1ccccc1)-c1ccccc1", "C[C@H](CC\\C=C(/C)C(O)=O)[C@H]1CC[C@@]2(C)C3=CC[C@H]4C(C)(C)[C@@H](O)CC[C@]4(C)C3=CC[C@]12C", "CCOC(=O)COc1ccc(CC=C)cc1OC" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "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": false, | |
| "local_files_only": false, | |
| "mask_token": "<mask>", | |
| "model_max_length": 128, | |
| "model_specific_special_tokens": { | |
| "boi_token": "<start_of_image>", | |
| "eoi_token": "<end_of_image>", | |
| "image_token": "<image_soft_token>" | |
| }, | |
| "pad_token": "<pad>", | |
| "padding_side": "right", | |
| "sp_model_kwargs": null, | |
| "spaces_between_special_tokens": false, | |
| "tokenizer_class": "GemmaTokenizer", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } | |