Instructions to use multimolecule/pangolin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/pangolin with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/pangolin") model = AutoModel.from_pretrained("multimolecule/pangolin") - Notebooks
- Google Colab
- Kaggle
File size: 1,248 Bytes
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"architectures": [
"PangolinModel"
],
"batch_norm_eps": 1e-05,
"batch_norm_momentum": 0.1,
"bos_token_id": null,
"context": 10000,
"dtype": "float32",
"eos_token_id": null,
"head": {
"act": null,
"bias": true,
"dropout": 0.0,
"hidden_size": 32,
"layer_norm_eps": 1e-12,
"loss_weight": null,
"num_labels": 4,
"output_name": null,
"problem_type": "regression",
"transform": null,
"transform_act": "gelu",
"type": null
},
"hidden_act": "relu",
"hidden_size": 32,
"id2label": null,
"label2id": null,
"mask_token_id": null,
"model_type": "pangolin",
"null_token_id": null,
"num_ensemble": 3,
"num_labels": 4,
"num_tissues": 4,
"output_contexts": false,
"pad_token_id": 4,
"problem_type": "regression",
"stages": [
{
"dilation": 1,
"kernel_size": 11,
"num_blocks": 4
},
{
"dilation": 4,
"kernel_size": 11,
"num_blocks": 4
},
{
"dilation": 10,
"kernel_size": 21,
"num_blocks": 4
},
{
"dilation": 25,
"kernel_size": 41,
"num_blocks": 4
}
],
"tie_word_embeddings": true,
"transformers_version": "5.7.0",
"unk_token_id": 4,
"vocab_size": 5
}
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