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# Models
[`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.
## PeftModel
[[autodoc]] PeftModel
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## PeftModelForSequenceClassification
A `PeftModel` for sequence classification tasks.
[[autodoc]] PeftModelForSequenceClassification
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## PeftModelForTokenClassification
A `PeftModel` for token classification tasks.
[[autodoc]] PeftModelForTokenClassification
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## PeftModelForCausalLM
A `PeftModel` for causal language modeling.
[[autodoc]] PeftModelForCausalLM
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## PeftModelForSeq2SeqLM
A `PeftModel` for sequence-to-sequence language modeling.
[[autodoc]] PeftModelForSeq2SeqLM
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## PeftModelForQuestionAnswering
A `PeftModel` for question answering.
[[autodoc]] PeftModelForQuestionAnswering
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## PeftModelForFeatureExtraction
A `PeftModel` for getting extracting features/embeddings from transformer models.
[[autodoc]] PeftModelForFeatureExtraction
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## PeftMixedModel
A `PeftModel` for mixing different adapter types (e.g. LoRA and LoHa).
[[autodoc]] PeftMixedModel
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## Utilities
[[autodoc]] utils.cast_mixed_precision_params
[[autodoc]] get_peft_model
[[autodoc]] inject_adapter_in_model
[[autodoc]] utils.get_peft_model_state_dict
[[autodoc]] utils.prepare_model_for_kbit_training
[[autodoc]] get_layer_status
[[autodoc]] get_model_status