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# Models
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[`PeftModel`] is the base model class for specifying the base Transformer model and configuration to apply a PEFT method to. The base `PeftModel` contains methods for loading and saving models from the Hub.
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## PeftModel
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[[autodoc]] PeftModel
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## PeftModelForSequenceClassification
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A `PeftModel` for sequence classification tasks.
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[[autodoc]] PeftModelForSequenceClassification
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## PeftModelForTokenClassification
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A `PeftModel` for token classification tasks.
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[[autodoc]] PeftModelForTokenClassification
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## PeftModelForCausalLM
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A `PeftModel` for causal language modeling.
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[[autodoc]] PeftModelForCausalLM
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## PeftModelForSeq2SeqLM
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A `PeftModel` for sequence-to-sequence language modeling.
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[[autodoc]] PeftModelForSeq2SeqLM
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## PeftModelForQuestionAnswering
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A `PeftModel` for question answering.
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[[autodoc]] PeftModelForQuestionAnswering
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## PeftModelForFeatureExtraction
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A `PeftModel` for getting extracting features/embeddings from transformer models.
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[[autodoc]] PeftModelForFeatureExtraction
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## PeftMixedModel
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A `PeftModel` for mixing different adapter types (e.g. LoRA and LoHa).
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[[autodoc]] PeftMixedModel
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## Utilities
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[[autodoc]] utils.cast_mixed_precision_params
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[[autodoc]] get_peft_model
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[[autodoc]] inject_adapter_in_model
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[[autodoc]] utils.get_peft_model_state_dict
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[[autodoc]] utils.prepare_model_for_kbit_training
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[[autodoc]] get_layer_status
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[[autodoc]] get_model_status
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