Models
Source: peft

<!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not berendered properly in your Markdown viewer.--># 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    - all## PeftModelForSequenceClassificationA `PeftModel` for sequence classification tasks.[[autodoc]] PeftModelForSequenceClassification    - all## PeftModelForTokenClassificationA `PeftModel` for token classification tasks.[[autodoc]] PeftModelForTokenClassification    - all## PeftModelForCausalLMA `PeftModel` for causal language modeling.[[autodoc]] PeftModelForCausalLM    - all## PeftModelForSeq2SeqLMA `PeftModel` for sequence-to-sequence language modeling.[[autodoc]] PeftModelForSeq2SeqLM    - all## PeftModelForQuestionAnsweringA `PeftModel` for question answering.[[autodoc]] PeftModelForQuestionAnswering    - all## PeftModelForFeatureExtractionA `PeftModel` for getting extracting features/embeddings from transformer models.[[autodoc]] PeftModelForFeatureExtraction    - all## PeftMixedModelA `PeftModel` for mixing different adapter types (e.g. LoRA and LoHa).[[autodoc]] PeftMixedModel    - all## 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