Instructions to use kvsr/peft-adapter-sequence-classification-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kvsr/peft-adapter-sequence-classification-binary with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("distilbert-base-uncased") model = PeftModel.from_pretrained(base_model, "kvsr/peft-adapter-sequence-classification-binary") - Notebooks
- Google Colab
- Kaggle
File size: 566 Bytes
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"_name_or_path": "distilbert-base-uncased",
"activation": "gelu",
"architectures": [
"DistilBertForSequenceClassification"
],
"attention_dropout": 0.1,
"dim": 768,
"dropout": 0.1,
"hidden_dim": 3072,
"initializer_range": 0.02,
"max_position_embeddings": 512,
"model_type": "distilbert",
"n_heads": 12,
"n_layers": 6,
"pad_token_id": 0,
"qa_dropout": 0.1,
"seq_classif_dropout": 0.2,
"sinusoidal_pos_embds": false,
"tie_weights_": true,
"torch_dtype": "float16",
"transformers_version": "4.34.0",
"vocab_size": 30522
}
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