Instructions to use multimolecule/mmsplice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/mmsplice with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/mmsplice") model = AutoModel.from_pretrained("multimolecule/mmsplice") - Notebooks
- Google Colab
- Kaggle
File size: 2,856 Bytes
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"acceptor_exon_length": 3,
"acceptor_intron_cut": 6,
"acceptor_intron_length": 50,
"architectures": [
"MMSpliceForSequencePrediction"
],
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"donor_exon_length": 5,
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"dtype": "float32",
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"head": {
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"bias": true,
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"hidden_size": 1,
"layer_norm_eps": 1e-12,
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"num_labels": 1,
"output_name": null,
"problem_type": "regression",
"transform": null,
"transform_act": "gelu",
"type": null
},
"hidden_size": 5,
"id2label": null,
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"mask_token_id": 4,
"model_type": "mmsplice",
"modules_config": {
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"dropout": 0.2,
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"hidden_sizes": [],
"pointwise_channels": 0,
"pool_mask_zeros": true,
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}
},
"null_token_id": 5,
"num_labels": 1,
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"problem_type": "regression",
"tie_word_embeddings": true,
"transformers_version": "5.7.0",
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"vocab_size": 4
}
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