Peft config.

Peft config Should it be CAUSAL_LM or SEQ_2_SEQ_LM or something else? Does it have any affect? The goal of my model is to parse an input for independent clauses in a sentence. json from transformers. 5 Oct 11, 2023 · Py之peft：peft(一款最先进的参数高效微调方法库)的简介、安装、使用方法之详细攻略 目录 peft的简介 peft的安装 peft的使用方法 peft的简介 参数有效微调(PEFT)方法使预训练语言模型(PLMs)能够有效地适应各种下游应用，而无需微调模型的所有参数。 Jul 5, 2024 · Py之peft：peft(一款最先进的参数高效微调方法库)的简介、安装、使用方法之详细攻略 目录 peft的简介 peft的安装 peft的使用方法 peft的简介 参数有效微调(PEFT)方法使预训练语言模型(PLMs)能够有效地适应各种下游应用，而无需微调模型的所有参数。 Dec 4, 2024 · You signed in with another tab or window. This does not look like a adapter_config. LoRA 是一种低秩分解方法，用于减少可训练参数的数量，从而加速大型模型的微调并减少内存使用。 在 PEFT 中，使用 LoRA 非常简单，只需设置 LoraConfig 并使用 get_peft_model() 包装它，即可创建一个可训练的 PeftModel。 Mar 26, 2023 · The way to train a PEFT model using PPO is to pass the PEFT config to the PPOTrainer, in your case you can load the peft config by doing PeftConfig. ref_model = AutoModelForCausalLM. prepare_model_inputs_fn_language_modeling is used by default. eva. Something must have gone wrong with the files when saving the model. PeftConfig，可选，默认为 None) — 用于包装模型的 PEFT 配置。 如果为 None ，则不包装模型。 用于群组相对策略优化 (GRPO) 方法的训练器。 然后，使用get_peft_model() 函数创建PeftModel，get_peft_model需要传入微调的model以及对应的PeftConfig。如果我们要了解模型中可训练参数的数量，我们可以使用 print_trainable_parameters 方法。 Feb 23, 2025 · pretrained_model_name_or_path 是from_pretrained的第一个参数，所以不加'pretrained_model_name_or_path='也可以。 注意device_map，如果不设置这个参数，默认放进cpu里 Apr 17, 2024 · Thanks. Dec 26, 2024 · get_peft_model 是 PEFT (Parameter-Efficient Fine-Tuning) 框架中的一个核心函数，通常用于加载或创建一个可以高效微调的模型，尤其适合在低资源场景或小型数据集上进行模型微调。 model_id (str or os. from_pretrained(model_id, **model_init_kwargs) elif peft_config is None: # If PEFT configuration is not provided, create a reference Prepare a model for training with a PEFT method such as LoRA by wrapping the base model and PEFT configuration with get_peft_model. prepare_model_inputs_fn_language_modeling。 PEFT, a library of parameter-efficient fine-tuning methods, enables training and storing large models on consumer GPUs. Dec 19, 2023 · You signed in with another tab or window. /my_peft_config_directory/). config. Wrap the base model with get_peft_model() to get a trainable PeftModel. PeftConfig, optional, defaults to None) — PEFT configuration used to wrap the model. To get started, import 🤗 Transformers to create the base model, 🤗 Datasets to load a dataset, 🤗 Evaluate to load an evaluation metric, and 🤗 PEFT to create a PeftModel and setup the configuration for p-tuning. md at main · huggingface/peft PEFT config classes Each PEFT method is specified by a PEFTConfig class which stores the types of adapters applicable to the PEFT method, as well as hyperparameters required to initialize these adapter modules. py file (as an example, this is the config file for LoRA) in the PEFT source code. When use_peft: true is set, the behavior differs depending on use_vllm. Setup. peft_type (Union[~peft. Any function defined here expects two arguments: model_input and peft_config. The main code snippet Feb 16, 2025 · Android Studio新建项目出错> Task:app:mergeDebugResources FAILED 报这个错去确实不清楚是个啥问题，最终解决问题的方法如下： 问题的原因是gradle版本和gradle插件版本不匹配，如下图： 如果将上面的插件如下配置，将不会出错： 较低版本在网上容易查，但是gradle5. 配置适配策略：使用get_peft_config()定义LoRA等方法的超参数（如r值、目标层）； 3. Oct 20, 2023 · The two adapters were obtained via fine-tuning with peft. Jul 26, 2023 · I am looking at a few different examples of using PEFT on different models. Trainer for the Group Relative Policy Optimization (GRPO) method. Oct 22, 2023 · 上記のように、peftを使用してLLMをファインチューニングする際には、1度読み込んだモデルをget_peft_modelという関数にモデルと peftの指定を行ったconfigを追加しないと行けません。 peft_type (Union[~peft. compute_metrics (Callable[[EvalPrediction], Dict], optional) — The function to use to compute the metrics. 🤗 Transformersは、いくつかのPEFT（Parameter Efficient Fine-Tuning）メソッドをネイティブにサポートしており、ローカルまたはHubに格納されたアダプターウェイトを簡単に読み込んで実行またはトレーニングできます。 model_id (str or os. 1) Wrapping base 🤗 Transformers model by calling get_peft_model 捷学知用 | 15 分钟快速上手微调 DeepSeek-R1阅读时间：15 分钟 TL;DR使用免费的 Colab，演示如何使用 huggingface-peft，trl 工具，使用 LoRA 在显存有限的情况下高效微调 DeepSeek-R1-Distill-Qwen-1. For any PEFT method, you’ll need to create a configuration which contains all the parameters that specify how the PEFT method should be applied. 12 22:06 浏览量：12 简介：本文介绍了在使用PEFT（Performance Evaluation Framework for Transformers）时遇到的 `ValueError: Please specify `target_modules` in `peft_config`` 错误的解决方案。 参数高效微调 (PEFT) 可以使预训练模型高效适应下游应用，而无需微调所有模型参数。 PEFT 支持广泛使用的大型语言模型低秩适应 (LoRA)。 为了从预训练的 Transformer 模型创建 LoRA 模型，我们导入并设置 LoraConf… May 11, 2023 · 首先推理代码 from peft import PeftModel model = PeftModel. /output/") 不应该指定具体checkpoint文件吗？ 指定了之后，报错Can't find 'adapter_config. For the bigscience/mt0-large model, you're only training 0. 1) 有关您可以调整的其他参数的更多详细信息，请参阅LoraConfig参考。 2. Model storage In some circumstances, you might want to store the whole PEFT model, including the base weights. By understanding each parameter and its role, you can fine-tune large models effectively, even on limited hardware. 5B，实现 F… Sep 4, 2023 · from transformers import AutoModel, AutoTokenizer from peft import PeftModel, PeftConfig # 加载peft配置 peft_model_id = "output_dir" peft_config = PeftConfig. from_pretrained(xxx) and pass that config to the trainer. If peft_type is not provided, the calling class type is instantiated. These methods only fine-tune a small number of extra model parameters, also known as adapters, on top of the pretrained model. This drastically reduces the number of parameters that need to be fine-tuned. The SFTTrainer class handles all the heavy lifting of creating the PEFT model using the peft config that is passed. We only need to create our LoraConfig and provide it to the trainer. AdaLora. Jan 3, 2024 · Describe the bug When checkpointing at defined steps, such as every 50 steps I get a 'CLIPTextModel' object has no attribute 'peft_config' while trying to save the model. Jul 22, 2023 · Unlock the power of QLoRA with our definitive guide! Learn how to fine-tune the Falcon-7b model using PEFT for optimal AI performance. 19% of the parameters! peft_config (~peft. This 2) Prefix Tuning(21年)在每一层加入一个embedding和一个MLP. The PEFT library is designed to help you quickly train large models on free or low-cost GPUs, and in this tutorial, you’ll learn how to setup a configuration to apply a PEFT method to a pretrained base model for training. Apr 21, 2025 · peft_config（PeftConfig，必填） PEFT 配置对象，指定使用的微调方法及其参数。 支持的配置类包括： LoraConfig（低秩适配） PromptTuningConfig（提示微调） PrefixTuningConfig（前缀微调） P-tuningConfig（P-Tuning） IA3Config（缩放向量微调） LoftQConfig（量化低秩适配） Therefore, if you would like to modify your PEFT configuration after having called [get_peft_model()] before, you would first have to unload the model with [~LoraModel. 使用 get_peft_model() 函数可以创建PeftModel。 Feb 10, 2023 · Creating config corresponding to the PEFT method; peft_config = LoraConfig( task_type=TaskType. For this example, we will be fine-tuning Llama-2 7b on a GPU with 16GB of VRAM. Despite there being a PEFT model (the model itself), the code reaches the peft_config is None part in grpo_trainer. For example, take a look at the following LoraConfig for applying LoRA and PromptEncoderConfig for applying p-tuning (these configuration files are already JSON-serialized). dataset_text_field : Field name in training dataset containing text data. Jul 13, 2023 · You signed in with another tab or window. from_pretrained(peft_model_id) # Load the base causal language model using the configuration This is the configuration class to store the configuration of a ~peft. We use the peft library from Hugging Face as well as LoRA to help us train on limited resources. ; prompt_tuning_init_text (str, optional) — The text to initialize the prompt embedding. lora. train(), SFTTrainer internally uses 🤗 Accelerate to prepare the model, optimizer and trainer using the DeepSpeed config to create DeepSpeed engine which is then trained. py:208: # Reference model if is_deepspeed_zero3_enabled(): self. 如果你是 🤗 peft 的新手，请从这里开始，了解该库的主要功能，以及如何使用 peft 方法训练模型。 操作指南 实用指南，演示如何在图像分类、因果语言建模、自动语音识别等不同类型的任务中应用各种 PEFT 方法。 Jul 19, 2023 · 本文将详细介绍peft和lora两种参数高效的微调方法，探讨其在深度学习领域的应用。通过对这两种方法的核心概念、数学模型、算法原理、应用实践以及优化方法进行全面剖析，本文旨在为读者提供对peft和lora的深入理解，并展示它们在实际项目中的价值。 问题一: LoRA modules_to_save参数和target_modules参该怎么写module名字，需要全名吗，还是只要后缀? 通过单步调试 get_peft_model(model, peft_config)这个函数，发现两个把参数初始化并设置为requires_grad=Tru… PEFT configuration and model. This class inherits from which contains the methods to push your model to the Hub. 🌍 PEFT contains parameter-efficient finetuning methods for training large pretrained models. peft 是一个参数高效微调方法库，可以在消费级 gpu 上训练和存储大型模型。 这些方法仅在预训练模型之上微调少量额外的模型参数，也称为适配器。 Sep 27, 2024 · PEFT LoraConfig makes the LoRA technique highly customizable and efficient. The initial phase can be understood as a step for pre-training the adapters so that when reducing their rank, there is already some information encoded that can be reduced instead of random matrices. Additive Quantization of Language Models is a Large Language Models compression method. As with other methods supported by PEFT, to fine-tune a model using IA3, you need to: Instantiate a base model. paper地址：Prefix-Tuning: Optimizing Continuous Prompts for Generation, P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Nov 27, 2023 · # Load the configuration for the Peft model from a pre-trained version peft_config = PeftConfig. CorDA. PeftType`], `str`]): The type of Peft method to use. After that, when you call trainer. QLoRA: QLoraPEFTConfig. Sep 12, 2024 · 一般设置为与 r 成比例的值 lora_dropout = 0. json' at 'output/checkpoint-400' 请问如何解决？ For example for language modeling the attention mask is used to determine which indices are padding tokens and should not be used for SVD. 13 以Qwen为例讲透参数高效微调（PEFT） 你好，我是黄佳。从今天起，我们将正式进入大模型微调实战。 大模型的微调，是一个对大模型的原理和实践经验要求都非常高的领域。 Aug 9, 2023 · from peft import LoraConfig, TaskType peft_config = LoraConfig (task_type = TaskType. Feb 13, 2024 · peft_config: LoRA configuration controlling model adaptation. tuners. Oct 11, 2024 · 然后，PEFT库是Hugging Face的一个参数高效微调库，支持多种方法，包括LoRA。那QLoRA应该也是PEFT支持的一种方法。需要确认一下PEFT是否支持QLoRA，可能需要查看文档。不过用户已经提到要结合PEFT库，所以应该支持。 接下来是Transformers Trainer，这个类提供了训练模型 Aug 30, 2023 · I am training a fine-tune of codellama using PEFT but not sure how to use the task_type parameter of LoraConfig. 2 PeftModel. PeftType, str]) — The type of Peft method to use. The base PeftModel contains methods for loading and saving models from the Hub, and supports the for prompt learning. You signed out in another tab or window. In some examples, the target modules are ["query_key_value&qu peft_config (Union[PeftConfig, dict[str, PeftConfig]]) — The adapter configuration object, it should be a dictionary of str to PeftConfig objects. For example for language modeling the attention mask is used to determine which indices are padding tokens and should not be used for SVD. Once the configuration is setup, pass it to the get_peft_model() function along with the base model to create a trainable PeftModel. If you pass a PEFT configuration, the model will be wrapped in a PEFT model. PEFT，全称为参数高效微调，是一个新兴的库，专为在资源受限的环境下高效适应大型预训练模型（如GPT、T5和BERT）而设计。其主要特点是在进行自然语言处理、计算机视觉和音频处理等任务时，只需微调模型的少量额外… 如果你对LoRA还没有一个直观的概念，可以回看这篇文章：《4. tokenizer : Pre-trained tokenizer used to prepare text data. Dec 3, 2024 · You signed in with another tab or window. unload] and then call [get_peft_model()] with your new configuration. Feb 3, 2025 · TL;DR. if use_peft: true and use_vllm: false Jul 19, 2023 · Llama 2 is a family of open-source large language models released by Meta. base_model_name_or_path) # 结合基础模型和微调结果，加载模型 Nov 8, 2024 · 本文将详细介绍peft和lora两种参数高效的微调方法，探讨其在深度学习领域的应用。通过对这两种方法的核心概念、数学模型、算法原理、应用实践以及优化方法进行全面剖析，本文旨在为读者提供对peft和lora的深入理解，并展示它们在实际项目中的价值。 peft_config (dict, defaults to None) — The PEFT configuration to use for training. The appropriate configuration type is determined by the peft_type argument. Feb 11, 2024 · Fine-tuning large language models (LLMs) like RoBERTa can produce remarkable results when adapting them to specific tasks. 8k次，点赞18次，收藏32次。参数高效微调PEFT(三)快速入门LoRA、AdaLoRA_perf微调 Mar 14, 2024 · 本文将详细介绍peft和lora两种参数高效的微调方法，探讨其在深度学习领域的应用。通过对这两种方法的核心概念、数学模型、算法原理、应用实践以及优化方法进行全面剖析，本文旨在为读者提供对peft和lora的深入理解，并展示它们在实际项目中的价值。 @dataclass class PeftConfig(PeftConfigMixin): """ This is the base configuration class to store the configuration of a [`PeftModel`]. The following five PEFT methods are currently supported: This method loads the configuration of your adapter model from a set of kwargs. This is the base configuration class for PEFT adapter models. This works great Common IA3 parameters in PEFT. Jul 12, 2024 · 总览 比起从零训练或是全量微调，使用 peft 库对预训练模型进行微调是更经济的做法。adapter 是 peft 独有的概念，可向预训练模型添加的额外的少量可学习参数。 peft 库是支持对同一基础模型附上多个 adapters 的，但文档写得不是很明了。本文针对需要对多个 adapters 的情 AutoPeftModel PEFT model PEFT types Configuration Tuner Adapters AdaLoRA IA3 Llama-Adapter LoHa LoKr LoRA X-LoRA LyCORIS Multitask Prompt Tuning OFT BOFT Polytropon P-tuning Prefix tuning Prompt tuning Layernorm tuning VeRA FourierFT VB-LoRA HRA CPT Bone Trainable Tokens 然后，使用get_peft_model() 函数创建PeftModel，get_peft_model需要传入微调的model以及对应的PeftConfig。如果我们要了解模型中可训练参数的数量，我们可以使用 print_trainable_parameters 方法。 Apr 17, 2024 · Thanks. Nov 21, 2023 · 本文将详细介绍peft和lora两种参数高效的微调方法，探讨其在深度学习领域的应用。通过对这两种方法的核心概念、数学模型、算法原理、应用实践以及优化方法进行全面剖析，本文旨在为读者提供对peft和lora的深入理解，并展示它们在实际项目中的价值。 from peft import LoraConfig, TaskType, get_peft_model from transformers import AutoModelForCausalLM # create LoRA configuration object lora_config = LoraConfig ( task_type = TaskType. 19%のみを peft_config (~peft. 加载预训练模型：通过AutoModelForCausalLM. The traditional paradigm is to finetune all of a model’s parameters for each downstream task, but this is becoming exceedingly costly and impractical because of the enormous number of parameters in models today. Here is a list of combinations I tried. Mar 29, 2023 · 以LORA为例，PEFT模型的使用非常方便，只需要按照原本的方式实例化模型，然后设置一下LORA的config，调用一下get_peft_model方法，就获得了在原模型基础上的PEFT模型，对于LORA策略来讲，就是在某些参数矩阵W的基础上增加了矩阵分解的旁支。在下面的例子中，选择 加载 PEFT adapter. My approach seems to be working, in the sense that there are no execution errors, the model seems to behave correctly, and model + adapter 1 + adapter 2 performs better than model + adapter 1 according to some metrics I'm using. You switched accounts on another tab or window. If None , the model is not wrapped. For the bigscience/mt0-large model Aug 8, 2023 · 使用get_peft_model 函数将基础模型和peft_config 包装起来，以创建PeftModel。要了解您模型中可训练参数的数量，可以使用print_trainable_parameters 方法。在这种情况下，您只训练了模型参数的0. from datasets import load_dataset from transformers import 可用于根据原始模型输入修改 SVD 计算的输入。例如，对于语言建模，注意力掩码用于确定哪些索引是填充令牌，不应用于 SVD。此处定义的任何函数都应接收两个参数：model_input 和 peft_config。默认情况下使用 peft. json文件和adapter权重，如上例所示。然后，您可以使用AutoModelFor类加载PEFT adapter模型。例如，要为因果语言建模加载一个PEFT adapter模型： 指定PEFT模型id peft_type (Union[~peft. formatting_func ( Optional[Callable] ) — Formatting function applied to the dataset before tokenization. PathLike) — The name of the PEFT configuration to use. Unfortunately, it can also be slow and computationally expensive. SEQ_2_SEQ_LM, inference_mode = False, r = 8, lora_alpha = 32, lora_dropout = 0. SEQ_2_SEQ_LM, inference_mode= False, r= 8, lora_alpha= 32, lora_dropout= 0. Create a configuration (LoraConfig) where you define LoRA-specific parameters. - peft/README. Nov 27, 2023 · Parameter-Efficient Fine-tuning (PEFT) is an innovative approach introduced by Hugging Face to address challenges associated with training and deploying large language models (LLMs) based The SFTTrainer supports a native integration with peft, which makes it super easy to efficiently tune LLMs using, e. 这些示例中的笔记本和脚本展示了如何使用低秩自适应 (lora) 以内存效率高的方式微调模型。 is the base model class for specifying the base Transformer model and configuration to apply a PEFT method to. As with other methods supported by PEFT, to fine-tune a model using LoRA, you need to: Instantiate a base model. json文件和adapter权重，如上例所示。然后，您可以使用AutoModelFor类加载PEFT adapter模型。例如，要为因果语言建模加载一个PEFT adapter模型： 指定PEFT Mar 29, 2023 · 以LORA为例，PEFT模型的使用非常方便，只需要按照原本的方式实例化模型，然后设置一下LORA的config，调用一下get_peft_model方法，就获得了在原模型基础上的PEFT模型，对于LORA策略来讲，就是在某些参数矩阵W的基础上增加了矩阵分解的旁支。在下面的例子中，选择 peft_config (~peft. Contribute to liuzard/transformers_zh_docs development by creating an account on GitHub. adapter 1 was obtained by fine-tuning model 1, while adapter 2 was obtained by fine-tuning model + adapter 1. Step into the future of machine learning today. May 25, 2023 · As best as I can tell, the LoraModel merge_and_unload attribute (peft/lora. AQLM quantization. Wrap the base model and peft_config with the [get_peft_model] function to create a [PeftModel]. A path to a directory containing a PEFT configuration file saved using the save_pretrained method (. The LoraConfig object contains a target_modules array. They can be used for a variety of tasks, such as writing… May 31, 2024 · 文章浏览阅读3. Mar 12, 2024 · 解决 `ValueError: Please specify `target_modules` in `peft_config`` 错误 作者： 暴富2021 2024. json from PEFT. Here is an example of a correct PEFT config file. Can be either: A string, the model id of a PEFT configuration hosted inside a model repo on the Hugging Face Hub. _hf_peft_config_loaded to True on successful lora load Sets the `_hf_peft_config_loaded` flag if a LoRA is successfully loaded in `load_lora_adapter`. They contain methods for saving and loading model configurations from the Hub, specifying the PEFT method to use, type of task to perform, and model configurations like number of layers and number of attention heads. . PEFT, a library of parameter-efficient fine-tuning methods, enables training and storing large models on consumer GPUs. It contains all the methods that are common to all PEFT adapter models. 19％！ The configuration classes stores the configuration of a , PEFT adapter models, and the configurations of PrefixTuning, PromptTuning, and . 03. prompt_tuning_init (Union[PromptTuningInit, str]) — The initialization of the prompt embedding. PEFT offers parameter-efficient methods for finetuning large pretrained models. However, I am having trouble getting a LoraModel type from my PeftModelForCausalLM. 1) 请参阅LoraConfig的参考文档，以获取更多关于您可以调整的其他参数的详细信息，比如目标模块或偏差类型等。 Quicktour. 认识 LoRA：从线性层到注意力机制》。 我们将在这里进一步探讨如何快速地在大型预训练模型中应用 LoRA，并解答可能存在的问题，包括： - peft 和 lora 之间有什么关系？. from_pretrained (peft_config. add_adapter(str(LoRA_index), peft_config Oct 23, 2023 · LoRA + Peft. from_pretrained(model, ". AdaLoRA has three phases defined by tinit, tfinal and total_step. The file you show looks like a config. Jan 25, 2025 · # use peft at your own risk; not working for me with multi-GPU training: trainer = GRPOTrainer (model = model, processing_class = tokenizer, reward_funcs = [xmlcount_reward_func, soft_format_reward_func, strict_format_reward_func, int_reward_func, correctness_reward_func], args = training_args, train_dataset = dataset, #peft_config=peft_config Mar 25, 2025 · …ad_lora_adapter` in PeftAdapterMixin class set self. 6. Train the PeftModel as you normally would train the Feb 14, 2025 · I’ve come across a potential issue and was wondering if anyone else has experienced it. 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. LoRA. 1) 使用 peft 与 trl 对 8 位模型进行低秩自适应（lora）微调的示例. Low-Rank Adaptation is a PEFT method that decomposes a large matrix into two smaller low-rank matrices in the attention layers. g. 1, # 在 LoRA 模块中应用 Dropout，防止过拟合，防止微调时模型过拟合到训练数据) # 应用 PEFT（LoRA）到预训练的模型上 model = get_peft_model (model, config) # 使用 get_peft_model 函数，将定义好的 LoRA 配置应用到预训练模型中 解释 May 23, 2023 · 旨在以一行代码便捷加载一个PEFT模型，而无需担心需要哪个确切的模型类或手动加载PeftConfig。PEFT 采用的高效做法是训练少量提示参数（Prompt Tuning）或使用低秩适应（LoRA）等重新参数化方法来减少微调时训练参数的数量。 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. Aug 8, 2023 · Another issue could be this: In this notebook, you first load the model, then LoRA is applied (via PEFT and trainer), which modifies model inplace. Supported PEFT models. One can also pass a PeftConfig object and a new adapter will be created with the default name adapter or create a new dictionary with a key adapter_name and a value of that peft config. Alternatively, you can re-initialize the model to ensure a fresh, unmodified state before applying a new Sep 16, 2023 · 使用get_peft_model函数将基础模型和peft_config包装起来，以创建PeftModel。要了解您模型中可训练参数的数量，可以使用print_trainable_parameters方法。在这种情况下，您只训练了模型参数的0. 要从huggingface的Transformers库中加载并使用PEFTadapter模型，请确保Hub仓库或本地目录包含一个adapter_config. if use_peft: true and use_vllm: false To check which keys and values are expected, check out the config. from datasets import load_dataset from transformers import PEFT, a library of parameter-efficient fine-tuning methods, enables training and storing large models on consumer GPUs. Create a configuration (IA3Config) where you define IA3-specific parameters. CorDA builds task-aware LoRA adapters from weight decomposition oriented by the context of downstream task to learn (instruction-previewed mode, IPM) or world knowledge to maintain (knowledge-preserved mode, KPM). Dec 26, 2024 · get_peft_model 是 PEFT (Parameter-Efficient Fine-Tuning) 框架中的一个核心函数，通常用于加载或创建一个可以高效微调的模型，尤其适合在低资源场景或小型数据集上进行模型微调。 Quicktour. 🤗 PEFT for setting up the LoRA configuration and creating the PEFT model; Copied. from peft import get_peft_model model = get_peft_model(model, peft_config) from peft import PeftModel, LoraConfig # 配置LoRA参数 rank = 4 LoRA_amount = 3 # 要添加的LoRA模块数量 peft_config = LoraConfig( inference_mode=False, r=rank, lora_alpha=32, lora_dropout=0. - huggingface/peft Huggingface transformers的中文文档. If you later call peft_model = get_peft_model(model, lora_config), you pass the modified model to PEFT again, not the original base model, which might lead to incorrect results (not sure). The setup requires just a few configuration steps: Define the LoRA configuration (rank, alpha, dropout) Create the SFTTrainer with PEFT config; Train and save the adapter weights [ ] Quicktour. P-Tuning: PtuningPEFTConfig Parameters . CAUSAL_LM , # type of task to train on inference_mode = False , # set to False for training r = 8 , # dimension of the smaller matrices lora_alpha = 32 Nov 30, 2023 · from peft import LoraConfig, TaskType peft_config = LoraConfig (task_type = TaskType. utils. Jan 28, 2025 · peft_config (~peft. Aug 14, 2024 · from peft import LoraConfig, TaskType peft_config = LoraConfig (task_type = TaskType. Must take a EvalPrediction and return a dictionary string to metric values. peft. PeftType, str]) — 要使用的 Peft 方法的类型。 这是 PEFT 适配器模型的基础配置类。 它包含所有 PEFT 适配器模型通用的方法。 For detailed instruction on using PiSSA, please follow these instructions. peft_config — 包含 Peft 模型参数的配置对象。 adapter_name (str, optional, 默认为 "default") — 要注入的 We'll use LoRA in our example, which combines LoRA with 4-bit quantization to further reduce memory usage without sacrificing performance. Common LoRA parameters in PEFT. autotrain-advanced fine tuning - Please specify `target_modules` in `peft_config` Feb 14, 2025 · I’ve come across a potential issue and was wondering if anyone else has experienced it. 1 ) # 初始化PeftModel并添加多个LoRA模块 model = PeftModel(model, peft_config, adapter_name="0") for LoRA_index in range(1, LoRA_amount): model. peft_config (~peft. Mar 14, 2025 · PEFT与 Transformers库 深度耦合，其核心流程分为三步： 1. The following five PEFT methods are currently supported: LoRA: LoraPEFTConfig. This guide walks through fine-tuning DeepSeek R1 using LoRA, a Parameter-Efficient Fine-Tuning (PEFT) method that updates only a small portion of model parameters to improve function calling. For example, it would insert a delimiter, such as in this sentence: “the tea was on the stove and was at high 随着，ChatGPT 迅速爆火，引发了大模型的时代变革。然而对于普通大众来说，进行大模型的预训练或者全量微调遥不可及。由此，催生了各种参数高效微调技术，让科研人员或者普通开发者有机会尝试微调大模型。 因此，… Apr 15, 2025 · Prepare a model for training with a PEFT method such as LoRA by wrapping the base model and PEFT configuration with get_peft_model. 19％！🤏. My current workflow is to define a pretrained model, define a LoraConfig, and use the get_peft_model function to being training. To get a sense of the number of trainable parameters in your model, use the [print_trainable_parameters] method. Let us know if this works 🤗 PEFT for setting up the LoRA configuration and creating the PEFT model; Copied. Each PEFT method is specified by a PEFTConfig class which stores the types of adapters applicable to the PEFT method, as well as hyperparameters required to initialize these adapter modules. 4对应的插件版本看来不宜过高，亲自尝试3. For detailed instruction on using PiSSA, please follow these instructions. from_pretrained()加载基础模型； 2. Reload to refresh your session. Once quantized, you can post-train GPTQ models with PEFT APIs. from_pretrained (peft_model_id) # 加载tokenizer tokenizer = AutoTokenizer. Apr 24, 2024 · I am trying to fine-tune phi-3 with autotrain-advanced. A configuration stores important parameters that specify how a particular PEFT method should be applied. py at main · huggingface/peft · GitHub) merges LoRA weights back into the main model. Args: peft_type (Union[[`~peft. peft_config (Dict, defaults to None) — The PEFT configuration to use for training. Create a configuration ( LoraConfig ) where you define LoRA-specific parameters. May 26, 2023 · PeftModelを作成するには、get_peft_model関数でベースモデルとpeft_configをラップします。モデルでトレーニング可能なパラメーター数の感覚を掴むには、print_trainable_parametersメソッドを使用します。このケースでは、モデルのパラメーターの0. jclk pytizjhq ymwvxdm vwehp sxhk yqzssi kiga kpr pvaw msxwdyq