Docs / PEFT: Add PEFT API documentation (huggingface#31078)

* add peft references

* add peft references

* Update docs/source/en/peft.md

* Update docs/source/en/peft.md

docs/source/en/peft.md

@@ -81,6 +81,8 @@ model = AutoModelForCausalLM.from_pretrained(model_id)
 model.load_adapter(peft_model_id)
 ```
 
+Check out the [API documentation](#transformers.integrations.PeftAdapterMixin) section below for more details.
+
 ## Load in 8bit or 4bit
 
 The `bitsandbytes` integration supports 8bit and 4bit precision data types, which are useful for loading large models because it saves memory (see the `bitsandbytes` integration [guide](./quantization#bitsandbytes-integration) to learn more). Add the `load_in_8bit` or `load_in_4bit` parameters to [`~PreTrainedModel.from_pretrained`] and set `device_map="auto"` to effectively distribute the model to your hardware:
@@ -227,6 +229,19 @@ lora_config = LoraConfig(
 model.add_adapter(lora_config)
 ```
 
+## API docs
+
+[[autodoc]] integrations.PeftAdapterMixin
+ - load_adapter
+ - add_adapter
+ - set_adapter
+ - disable_adapters
+ - enable_adapters
+ - active_adapters
+ - get_adapter_state_dict
+
+
+
 
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 TODO: (@younesbelkada @stevhliu)