Instructions to use multimolecule/basset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/basset with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/basset") model = AutoModel.from_pretrained("multimolecule/basset") - Notebooks
- Google Colab
- Kaggle
File size: 1,058 Bytes
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"architectures": [
"BassetForSequencePrediction"
],
"batch_norm_eps": 1e-05,
"batch_norm_momentum": 0.1,
"bos_token_id": 1,
"conv_channels": [
300,
200,
200
],
"conv_kernel_sizes": [
19,
11,
7
],
"conv_pool_sizes": [
3,
4,
4
],
"dtype": "float32",
"eos_token_id": 2,
"fc_sizes": [
1000,
1000
],
"head": {
"act": null,
"bias": true,
"dropout": 0.0,
"hidden_size": 1000,
"layer_norm_eps": 1e-12,
"loss_weight": null,
"num_labels": 164,
"output_name": null,
"problem_type": "multilabel",
"transform": null,
"transform_act": "gelu",
"type": null
},
"hidden_act": "relu",
"hidden_dropout": 0.3,
"hidden_size": 1000,
"id2label": null,
"label2id": null,
"mask_token_id": 4,
"model_type": "basset",
"null_token_id": 5,
"num_conv_layers": 3,
"num_labels": 164,
"pad_token_id": 0,
"sequence_length": 600,
"tie_word_embeddings": true,
"transformers_version": "5.7.0",
"unk_token_id": 3,
"vocab_size": 4
}
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