Sentence Similarity
sentence-transformers
Safetensors
modchembert
cheminformatics
smiles
molecular-similarity
feature-extraction
dense
Generated from Trainer
dataset_size:19381001
loss:Matryoshka2dLoss
loss:MatryoshkaLoss
loss:TanimotoSentLoss
custom_code
Eval Results (legacy)
Instructions to use Derify/ChemMRL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Derify/ChemMRL with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Derify/ChemMRL", trust_remote_code=True) sentences = [ "COC(=O)c1sc(-c2ccc(C)cc2)c2c1NC(=O)C2(c1ccccc1)c1ccccc1", "COC(=O)c1sc(Nc2ccc(Br)cn2)c2c1NC(=O)C2(c1ccccc1)c1ccccc1", "CC[NH+]1CCOC(C(NN)c2ccccc2Br)C1", "CC([NH2+]C(C)c1ccccc1)C(=O)P(C)C(C)(C)C" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 1,609 Bytes
0417ad2 | 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 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | {
"architectures": [
"ModChemBertModel"
],
"attention_bias": false,
"attention_dropout": 0.1,
"auto_map": {
"AutoConfig": "configuration_modchembert.ModChemBertConfig",
"AutoModel": "modeling_modchembert.ModChemBertModel",
"AutoModelForMaskedLM": "modeling_modchembert.ModChemBertForMaskedLM",
"AutoModelForSequenceClassification": "modeling_modchembert.ModChemBertForSequenceClassification"
},
"bos_token_id": 0,
"classifier_activation": "gelu",
"classifier_bias": false,
"classifier_dropout": 0.0,
"classifier_pooling": "max_seq_mha",
"classifier_pooling_attention_dropout": 0.1,
"classifier_pooling_last_k": 5,
"classifier_pooling_num_attention_heads": 4,
"cls_token_id": 0,
"decoder_bias": true,
"deterministic_flash_attn": false,
"dtype": "bfloat16",
"embedding_dropout": 0.1,
"eos_token_id": 1,
"global_attn_every_n_layers": 3,
"global_rope_theta": 160000.0,
"hidden_activation": "gelu",
"hidden_size": 1024,
"initializer_cutoff_factor": 2.0,
"initializer_range": 0.02,
"intermediate_size": 1536,
"layer_norm_eps": 1e-05,
"local_attention": 8,
"local_rope_theta": 10000.0,
"max_position_embeddings": 512,
"mlp_bias": false,
"mlp_dropout": 0.1,
"model_type": "modchembert",
"norm_bias": false,
"norm_eps": 1e-05,
"num_attention_heads": 16,
"num_hidden_layers": 22,
"pad_token_id": 2,
"position_embedding_type": "absolute",
"repad_logits_with_grad": false,
"sep_token_id": 1,
"sparse_pred_ignore_index": -100,
"sparse_prediction": false,
"transformers_version": "4.57.1",
"vocab_size": 2362
}
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