Peft tasktype github 1,transformers=4. backends. You can see that the entry for gemma in TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING is ["q_proj", "v_proj"]. from . 2 python--3. I'm training a reward model and I just need Lora some linear for the base model. 0 bitsandbytes-0. GitHub Gist: instantly share code, notes, and snippets. 9. TOKEN_CLS Dec 8, 2023 · Saved searches Use saved searches to filter your results more quickly 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. Let's use an example. density/num_tunable_weights set the number of tunable parameters as a proportion of total model params / as an absolute number respectively. 我们在 GitHub PEFT 库中探索了许多有趣的用例。 以下罗列的是其中最有趣的: 使用 🤗 PEFT LoRA 在具有 11GB RAM 的消费级硬件上调整 bigscience/T0_3B 模型 (30 亿个参数)，例如 Nvidia GeForce RTX 2080 Ti、Nvidia GeForce RTX 3080 等，并且使用 🤗 Accelerate 的 DeepSpeed 集成: peft_lora_seq2seq_accelerate_ds_zero3_offload. - huggingface/peft Mar 26, 2023 · It seems that PEFT currently requires the user to specify a TaskType in the LoraConfig, which does not include the base PreTraineModel that outputs just the hidden states. - huggingface/peft peft. 0 Who can help? @EricLBuehler Information The official example scripts My own modified scripts Tasks An officially supported task in the examples folder My own task or dataset (give details below) Reproduction Code Jun 13, 2023 · The tutorial works fine but when i tried to modify it to perform a Classification task on a standard Input_ids, ClassLabel tokenized dataset i got Trainer initialization errors related to ConstantLengthDataset assumptions in the SFT code Fine-tuning large pretrained models is often prohibitively costly due to their scale. 0 accelerate-0. 前言¶. SEQ_2_SEQ_LM: Sequence-to-sequence language modeling. Feb 26, 2024 · System Info TypeError: LoraConfig. Overview of the supported task types: SEQ_CLS: Text classification. Prepare a model for training with a PEFT method such as LoRA by wrapping the base model and PEFT configuration with get_peft_model. Apr 19, 2023 · I'm tring to applied LoRA to M2M100. /peft/utils/init. 1 transformers==4. However, when I use peft==0. 1 in 5-10 epochs according to learning rate. SEQ_2_SEQ_LM, inference_mode=False, r=8, lora_alpha=32, lora_dropout=0. 🤗 peft（参数高效微调）是一个用于高效地将大规模预训练模型适配到各种下游应用的库。. 4. 最近开源的大模型越来越多，但是针对我们个人来说，从零开始训练一个大模型的成本太高，因此我们介绍一个针对大模型的高效微调框架-peft Jan 21, 2025 · However, when I did full-parameter supervised fine-tuning without using peft, the final results on the independent test set were all normal. Dec 20, 2024 · from peft import get_peft_model, LoraConfig, TaskType from transformers import CLIPModel # Load the pre-trained CLIP model model = CLIPModel. Dec 20, 2023 · @BenjaminBossan Big thanks for the quick confirmation! I'm quite relieved. SEQ_2_SEQ_LM, inference_mode= False , r= 8 , lora_alpha= 32 , lora_dropout= 0. py. from_pretrained (model_name) # Define the PEFT configuration peft_config = LoraConfig ( task_type = TaskType. In A short sample of models families available to be trained with PEFT are: Bloom, Llama, GPT-J, GPT-2, BERT and more. Feature request. This has the least amount of side effects, but future PEFT versions may require additional parameters, so this solution is not quite as robust as the next. 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。 Feb 20, 2024 · Feature request 'PeftModelForSequenceClassification' is not supported for text-classification when using huggingface pipeline. - peft/src/peft/auto. You signed out in another tab or window. The official example scripts; My own modified scripts; Tasks. Below is one approach: from peft import get_peft_config, get_peft_model, LoraConfig, TaskType lora_config = LoraConfig( task_type='CAUSAL_LM', inference_mode=Fa 由于本系列文章主要针对 Huggingface 开源的 PEFT 库进行讲解；因此，本文先对其进行概述以及环境搭建。 PEFT 概述. Back to blog 珞 PEFT: Parameter-Efficient Fine-Tuning of Billion-Scale Models on Low-Resource Hardware Published February 10, 2023. 1+cu116 peft--0. 3. Feb 15, 2025 · You signed in with another tab or window. sequence classification, multiple choice tasks: TaskType. 15 torch==2. py at main · huggingface/peft System Info peft = 0. 3 transformers==4. 0, fine-tuning ChatGLM3-6B causes the model to become dumb with a loss of 0 When peft>=0. 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。 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. Aug 4, 2023 · Saved searches Use saved searches to filter your results more quickly Nov 18, 2023 · Hi @estuday Thanks for the issue, I can see many potential things that could cause issues here, but not sure what would be the exact fix 1- you are using T5ForConditionalGeneration which is a seq2seq model on TaskType. AdaLora. Nov 7, 2024 · Feature request The current implementation of LoraConfig in the PEFT library does not validate whether the provided task_type is valid. Hugging Face is working hard to bring more Models to the Library. 9 Who can help? / 谁可以帮助到您？ @Btlmd 是在PEFT微调过程中出现的问题 Information / 问题信息 The official example scripts / 官方的示例脚本 My own Save storage by avoiding full finetuning of models on each of the downstream tasks/datasets, With PEFT methods, users only need to store tiny checkpoints in the order of MBs all the while retaining performance comparable to full finetuning. 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 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. I'm running inference on 3x v100 GPUs with full precision (not bf16 or fp16) When I use model. seq_cls：文本分类。 seq_2_seq_lm：序列到序列语言建模。 Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters. SEQ_2_SEQ_LM, num_virtual May 20, 2024 · from peft import get_peft_config, get_peft_model, PrefixTuningConfig, TaskType, PeftType cannot import name 'get_peft_config' from 'peft' (unknown location) The text was updated successfully, but these errors were encountered: Jun 5, 2024 · 1. Aug 8, 2023 · from peft import LoraConfig, TaskType peft_config = LoraConfig(task_type=TaskType. For example, to train with LoRA, load and create a [LoraConfig] class and specify the following parameters: from peft import LoraConfig, TaskType peft_config = LoraConfig (task_type=TaskType. 0, loss is always NAN. save( get_peft_model_state_dict(model, state_d Apr 3, 2024 · Feature request When ever I am using peft_config = PrefixTuningConfig( peft_type="PREFIX_TUNING", inference_mode=False, task_type=TaskType. Information. 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). 7. deterministic = True torch May 1, 2023 · from peft import get_peft_model from transformers import AutoModelForSeq2SeqLM, AutoTokenizer from peft import LoraConfig, TaskType, PromptTuningConfig, PromptTuningInit import torch model_name_or_path = "google/flan-t5-small" tokenizer_name_or_path = "google/flan-t5-small" model = AutoModelForSeq2SeqLM. 46. - huggingface/peft peft 支持的不同类型任务的枚举类。 支持的任务类型概述. CAUSAL_LM: Causal language modeling. 8) Who can help? @BenjaminBossan Information The official example scripts My own modified scripts Tasks An officially supported task in the examples folder My own task or dataset (give d Mar 3, 2024 · Hi! I tried to do lora with llama2 model. - huggingface/peft Fine-tuning large pretrained models is often prohibitively costly due to their scale. - huggingface/peft May 4, 2023 · I wish to use peft for Question Answering, but it isn't available as an available tasktype. cudnn. Reload to refresh your session. Motivation Jun 25, 2023 · Describe the bug 执行from peft import LoraConfig, TaskType, get_peft_model, PeftModel, prepare_model_for_int8_training时报错 RuntimeError: CUDA Setup failed despite GPU being available. model. 35. 0, fine-tuning ChatGLM3-6B causes the model to become dumb with a loss of 0 Apr 11, 2024 System Info peft==0. 34. 31. json file, there's a description about the updated target_modules info, in the case forTaskType. from_pretrained) to spit out the adapter. The required changes are shown in the code block below. Supervised Fine-tuning is used for… May 20, 2024 · from peft import get_peft_config, get_peft_model, PrefixTuningConfig, TaskType, PeftType cannot import name 'get_peft_config' from 'peft' (unknown location) The text was updated successfully, but these errors were encountered: Mar 31, 2024 · System Info When ever I am using peft_config = PrefixTuningConfig( peft_type="PREFIX_TUNING", inference_mode=False, task_type=TaskType. 由于微调模型的所有参数成本高昂且难以实现，而 peft 方法只需要微调少量额外模型参数，从而显著降低了计算和存储成本，同时实现了与模型全量微调近乎相当的性能。 Hi, sorry I can not share the whole code but a snippet of what I do on the git_vatex_base_model from hugging face. 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. - huggingface/peft Mar 22, 2023 · Parameter-Efficient Fine-Tuning using 🤗 PEFT. SQL_CLS, but then you run into another issues: 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. Contribute to Yubo8Zhang/PEFT development by creating an account on GitHub. Also, why I am hitting ValueError: Target modules ['q', 'v'] not found in the base model. from_pretrained(output_dir) # model = get_peft_model(model, lora_config) from peft import AutoPeftModelForCausalLM # To perform inference on the test dataset example load the model from the checkpoint: persisted_model = AutoPeftModelForCausalLM. lora_A. Qwen2-VL是阿里通义实验室最新推出的多模态大模型。本文我们将简要介绍基于 transformers、peft 等框架，使用 Qwen2-VL-2B-Instruct 模型在COCO2014图像描述 上进行Lora微调训练，同时使用 SwanLab监控训练过程与评估模型效果。 本节使用的 Jun 12, 2023 · You signed in with another tab or window. May 20, 2024 · from peft import get_peft_config, get_peft_model, PrefixTuningConfig, TaskType, PeftType cannot import name 'get_peft_config' from 'peft' (unknown location) The text was updated successfully, but these errors were encountered: Apr 3, 2024 · Feature request When ever I am using peft_config = PrefixTuningConfig( peft_type="PREFIX_TUNING", inference_mode=False, task_type=TaskType. The losses are not 100% the same but basically not changing a lot: for comparison by fine-tuning of the base model the losses decreases from ~11 to 0. May 18, 2023 · Hi, is it possible to use PEFT with my custom classification head? The thing is that I have my custom classification Head and I want to fine-tune the underlying Transformer model along with the classification head. But, seeing the TaskType in PeftConfig got me thinking -- "mhmmm, I bet this is used for something important, though I have no clue what, let me loo 2) Prefix Tuning(21年)在每一层加入一个embedding和一个MLP. question answering task: TaskType. 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. 0 transformers--4. init() got an unexpected keyword argument 'use_original_init' Who can help? No response Information The official example scripts My own modified scripts Tasks My own task or dataset (give details below) # from peft import LoraConfig, get_peft_model # lora_config = LoraConfig. 19% of the parameters! task_type=TaskType. I'm not sure how should I proceed in that case? Could it be an additional feature in a future release? 学习huggingface 的PEFT库. 0 peft==0. Brief introduction to LoRA Tuning. Mar 25, 2024 · System Info in documentation it is "QUESTION_ANS = "QUESTION_ANS"" but it doesnt work, i test the same code for CASUAL_LM , it works, hence needs to be fixed, I tried "QUESTION_ANSWERING" that does work as wellthe Who can help? Aug 9, 2023 · I wanted to use peft (specifically, LoRA) for a task that is not included as a TaskType. Why? Who can help? No response. 13. 5. Request: add support. The following hyperparameters can be modified through the SftConfig:. 11. Error: ValueError: fp16 is enabled but the following parameters have dtype that is not fp16: base_model. I'm trying to train a LLM to perform NER on some text lines. peft 支持的不同类型任务的枚举类。 支持的任务类型概述. Should it be CAUSAL_LM or SEQ_2_SEQ_LM or something else? Does it have any affect? The goal of my model is… Each PEFT method is defined by a [PeftConfig] class that stores all the important parameters for building a [PeftModel]. Alternatively, you can re-initialize the model to ensure a fresh, unmodified state before applying a new Feb 13, 2023 · You signed in with another tab or window. 先来说 soft prompt 的配置信息，它的 prompt 内容不需要人为指定，是让模型自己去学的，所以用num_virtual_tokens指定prompt长度就可以创建简单的 soft prompt。 This is the configuration class to store the configuration of a ~peft. For token classification it is TOKEN_CLS and for sequence classification it is SEQ_CLS. An officially supported task in the examples folder; My own task or dataset (give details below) Reproduction. 3 Who can help? No response Information The official example scripts My own modified scripts Tasks An officially suppo Jan 30, 2024 · Been having issues w/trying to use a PEFT configuration for my PPO training. from transformers import AutoModelForSeq2SeqLM from peft import get_peft_model Jun 6, 2023 · 背景学习一下huggingface的peft的代码。 peft = parameter efficient fine-tuning。 鉴于最近大火的qlora等技术的崛起，低cost来微调大模型的趋势，不可阻挡了。 自己folk了一下peft库，加了一些注释而已。 GitHub… Feb 22, 2023 · After fine-tuning a flan t5 11b model on custom data, I was saving the checkpoint via accelerate like this accelerator. - huggingface/peft Jun 14, 2023 · System Info torch==2. This can lead to silent failures when users accidentally provide a misspelled or unsupported task typ 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. . ACL ARR 2025 Feb. FEATURE_EXTRACTION: Feature extraction. 0. You signed in with another tab or window. Fine-tuning large pretrained models is often prohibitively costly due to their scale. SEQ_2_SEQ_LM, inferen Mar 23, 2023 · Training Model loaded from scratch - No OOM: pretrained= 'google/flan-t5-xl' model = AutoModelForSeq2SeqLM. attention. I think it must have something to do with how GitHub outcompletes, so people type "@saya" and then "@sayakpaul" is suggested and they hit enter but for some reason only "@saya" is entered. 1 Python: 3. I'm curious if there are significant differences in Lora between different versions? 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 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. Say your model is gemma and you want to use LoRA. 26. 3 Who can help? @Rocketknight1 @gante Information The official example scripts My own modified scripts Tasks An officially supported task in th We have "sayakpaul" but I honestly don't know why people are constantly pinging you. query_key_value. 1 . - huggingface/peft Aug 2, 2024 · You signed in with another tab or window. Contribute to liuzard/transformers_zh_docs development by creating an account on GitHub. I changed different tasks, changed different peft methods, changed different parts of fine-tuning, and used the latest version of peft and still can't solve the problem. When using PEFT with a LoraConfig to train a SequenceClassification model there should be a way to save the adapter weight matrices added by LoRA inside the attention blocks, as well as the classification head added for the classification task, which is also tuned as part of the training process. 2 Who can help? @pacman100 Information The official example scripts My own modified scripts Tasks An officially supported task in the examples Fine-tuning large pretrained models is often prohibitively costly due to their scale. unload] and then call [get_peft_model()] with your new configuration. 01. 10. 30. 2. gpt_neox. 0+cu121 peft==0. Mar 18, 2024 · Tangent-90C changed the title When peft>0. TOKEN_CLS: Token classification. Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all GitHub - huggingface/peft: 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. PEFT 是 Huggingface 开源的一个参数高效微调库，它提供了最新的参数高效微调技术，并且可以与 Transformers 和 Accelerate 进行无缝集成。 支持的高效微调 Aug 6, 2023 · I have fine-tuned the model using Lora, the config is available here: "Lukee4/biogpt-2020_2labels" I used BioGPTforSequenceClassification and the fine-tuning worked Apr 27, 2023 · do I set the task_type=TaskType. QUESTION_ANS. Without going into further details, a doubt came to me: which task_type should I set for LoraConfig? SEQ_CLS, SEQ_2_SEQ_LM, CAUSAL_LM, TOKEN_CLS, QUESTION_ANS, FEATURE_EXTRACTION. Feb 26, 2023 · Hi all, I am having an issue when running Peft LoRA with DeepSpeed Zero3. SEQ_2_SEQ_LM, num_virtual Oct 17, 2024 · import torch from sentence_transformers import SentenceTransformer from peft import get_peft_model, PromptTuningConfig, TaskType, PromptTuningInit # Initialize the model model_name = "bert-base-uncased" model = SentenceTransformer (model_name) # Apply PEFT with PromptTuningConfig peft_config = PromptTuningConfig ( task_type = TaskType. Mar 25, 2023 · Thanks to PEFT-LORA I was able to fine-tune a 20B FLAN-UL2 model. Each PEFT method is defined by a PeftConfig class that stores all the important parameters for building a PeftModel. Expose the specific needed arguments ("solution 1" in the snippet above). 1 soft prompt. md at main · huggingface/peft 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. 0, loss is normal. 40. You switched accounts on another tab or window. Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all the model's parameters. 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 Setup. SEQ_2_SEQ_LM, num_virtual Jun 5, 2024 · 1. from_pretrained (model_name) image_processor Apr 14, 2023 · Expected behavior. AdaLoRA has three phases defined by tinit, tfinal and total_step. The peft support for Llama models is already present for Causal LM. 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. seq_cls：文本分类。 seq_2_seq_lm：序列到序列语言建模。 Contribute to AlanAnsell/peft development by creating an account on GitHub. 1 Who can help? @pacman100 @youn Information The official example scripts My own modified scripts Tasks An officially supported task in the examples folder (such 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. TOKEN_CLS? Hi! You can find the available TaskType's here. Also although It's a bit late, for those who may come to the same question, I found in the trained model, within the adapter_config. CAUSAL_LM, please consider using TaskType. 0 Information The official example scripts My own modified scripts Code Information Group Query Attention has been used in LlamaAttention (transformers==4 Jul 6, 2024 · Frustrated by the maze of parameters in LLM fine-tuning? Confused by Hugging Face’s PEFT library? Let’s cut through the jargon and understand fine-tuning. float16, low_cpu_mem_usage = True) lora_config = LoraConfig ( task_type Mar 10, 2015 · System Info Python v3. py。 Huggingface transformers的中文文档. If doing model sharding (FSDP, ZeRO 3) you might need to make some changes, but the general gist is: get the PyTorch module (the model) to be the same as the one used for training, load the state dict from the Trainer checkpoint onto it, then you can use the usual peft stuff (. - huggingface/peft 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，… May 9, 2024 · System Info transformers-4. 1、背景介绍. Jun 8, 2024 · System Info peft, transformers, pytorch, python (3. utils import 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. 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. generate() with the PEFT-Model it is about 10 times slower. we You signed in with another tab or window. Jan 13, 2025 · System Info Original model architecture: EsmForSequenceClassification( (esm): EsmModel( (embeddings): EsmEmbeddings( (word_embeddings): Embedding(33, 640, padding_idx The usage is almost identical to LoRA in the PEFT library, with some extra configuration parameters in RosaConfig + a single line of code adding a RosaScheduler. 1 Who can help? @pacman100 @youn Information The official example scripts My own modified scripts Tasks An officially supported task in the examples folder (such Mar 13, 2024 · You can check the default target_module in this file and modify it according to your needs. This quicktour will show you PEFT’s main features and how you can train or run inference on large models that would typically be inaccessible on consumer devices. Aug 29, 2023 · Feature request. from_pretrained(model_name_or_path) peft_config = PromptTuningConfig( task_type=TaskType Dec 11, 2023 · import torch from transformers import AutoModelForCausalLM, AutoTokenizer from peft import PeftModel, TaskType, LoraConfig, get_peft_model tok = AutoTokenizer. wait_for_everyone() accelerator. QUESTION_ANS: Question answering. It seems one can workaround this by providing any task type like TaskType. May 3, 2023 · PEFT training. 현재(24. 0, when I use peft==0. For the bigscience/mt0-large model, you're only training 0. Supervised Fine-tuning is used for… This is the configuration class to store the configuration of a ~peft. Train. Feb 26, 2025 · from datasets import load_dataset from peft import LoraConfig, TaskType, PeftModel from sentence_transformers import ( SentenceTransformer, SentenceTransformerTrainer Apr 20, 2023 · All of the forward() calls for the different peft models use a labels field, so I don't think there's a different TaskType I could have chosen which would not have this issue. Fine-tuning large-scale PLMs is often prohibitively costly. 43. from_pretrained(output_dir, 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. 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. Jul 6, 2024 · Frustrated by the maze of parameters in LLM fine-tuning? Confused by Hugging Face’s PEFT library? Let’s cut through the jargon and understand fine-tuning. 1 Who can help? No response Information The official example scripts My own modified scripts Tasks An officially supported task in the examples folder My own task or dataset (g Nov 26, 2023 · System Info / 系統信息 torch--1. layers. 1 peft-0. from_pretrained ("llama2-7b") model = AutoModelForCausalLM. SEQ_CLS. Contribute to dddd-d/Debiasing-the-Fine-Grained-Classification-Task-in-LLMs-with-Bias-Aware-PEFT development by creating an account on GitHub. SEQ_2_SEQ_LM. sequence labeling task: TaskType. config import PeftConfig, PeftType, PromptLearningConfig, TaskType @ . - peft/README. My approach in the models we built so far is to get the embedding from the model, then backprop into the RobertaModel based on the errors of the downstream task to HiTaskType should be consistent with PEFT TaskType. It seems that any one of TaskType is suitable. 0 accelerate==0. 1 evaluate-0. - huggingface/peft Mar 25, 2023 · Thanks to PEFT-LORA I was able to fine-tune a 20B FLAN-UL2 model. from peft. Please check the target modules and try again. - huggingface/peft Mar 26, 2024 · import torch from peft import LoraConfig, TaskType, get_peft_model, prepare_model_for_kbit_training from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig, TrainingArguments, AutoConfig import argparse parser = argparse. This significantly decreases the computational and storage costs. - peft/tests/test_torch_compile. Jul 2, 2024 · import torch from datasets import load_dataset from transformers import ( AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, HfArgumentParser, TrainingArguments, logging, ) from peft import LoraConfig, peft_model, TaskType from trl import SFTTrainer, SFTConfig # fix random sequence torch. 2 transformers==4. In this regard, PEFT methods only fine-tune Jan 9, 2025 · import torch from transformers import AutoImageProcessor, Dinov2WithRegistersModel from peft import LoraConfig, get_peft_model, TaskType def setup_peft_model (model_name = "facebook/dinov2-with-registers-large", lora_r = 8, lora_alpha = 32, lora_dropout = 0. 20. 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. Enum class for the different types of tasks supported by PEFT. - huggingface/peft Nov 9, 2024 · You signed in with another tab or window. 1): base_model = Dinov2WithRegistersModel. - huggingface/peft May 3, 2023 · PEFT training. from transformers import AutoModelForSeq2SeqLM, AutoTokenizer from peft import get_peft_config, get_peft_model, LoraConfig, TaskType peft_config = LoraConfig(task_type = TaskType. CAUSAL_LM for llama the default setting is as expected just like below: Oct 21, 2024 · TaskType里还支持很多类型的任务，不过CAUSAL_LM基本支持各类 peft 方法，其他任务不一定。. py at main · huggingface/peft Apr 21, 2023 · Works with LLaMA trained with DeepSpeed ZeRO 1. - huggingface/peft Aug 9, 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。 Mar 31, 2024 · System Info When ever I am using peft_config = PrefixTuningConfig( peft_type="PREFIX_TUNING", inference_mode=False, task_type=TaskType. 12)는 11개의 PeftType과 6개의 TaskType이 존재한다. Jan 15, 2024 · System Info peft==0. from_pretrained(pretrained,low_cpu_mem_usage=True) Nov 1, 2023 · System Info Transformers Version: 4. It would be good to have support it for Sequence Classification as the modeling file of Llama in HuggingFace has definitions for both Causal LM and Sequence Classification. from_pretrained ("llama2-7b", torch_dtype = torch. Apr 15, 2025 · Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all the model's parameters. 1,accelerate=0. pxejxwevktfahozipyuzkauhjcsmaychneixblbnhspvzyshpkd