1、一种新的正则化方法AD-DROP可以缓解大模型微调在小数据集上过拟合问题。微调大型预训练语言模型（LL...
py #lora方法核心的Class定义文件 |-- model.py #llama 模型定义文件 2.1 MergedLinear源码解析 LoRA方法核心的Class--MergedLinear代码解析,为了节省篇幅我对代码做了些裁剪,这部分代码在lit_llama/lora.py, 完整源码可去github上查看 # 这是带LoRA方法的并且融合了生成QKV三个Linear的Class class MergedLinear(...
base_model:openlm-research/open_llama_3b_v2model_type:LlamaForCausalLMtokenizer_type:LlamaTokenizerload_in_8bit:trueload_in_4bit:falsestrict:falsepush_dataset_to_hub:datasets:-path:teknium/GPT4-LLM-Cleanedtype:alpacadataset_prepared_path:val_set_size:0.02adapter:loralora_model_dir:sequence_len:1...
github链接:https://github.com/google-research/text-to-text-transfer-transformer#released-model-checkpoints huggingface链接:https://huggingface.co/docs/transformers/model_doc/flan-t5 本文分析了使用“指令数据”对语言模型进行微调所带来的改进,涉及缩放 :1)增加微调任务,2) 增大模型大小,以及 (3) 添加思维...
To learn about Int8 quantization, refer to LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale. Fully Sharded Data Parallel (FSDP) –This is a type of data-parallel training algorithm that shards the model’s parameters across data parallel workers and can opti...
论文题目:《Scaling Instruction-Finetuned Language Models》 论文链接:https://arxiv.org/pdf/2210.11416.pdf github链接:https://github.com/google-research/text-to-text-transfer-transformer#released-model-checkpoints huggingface链接:https://huggingface.co/docs/transformers/model_doc/flan-t5 ...
base_dir: '/opt/llm_finetune/' vi config/model_info.yaml 注意:(初始化的大模型需要手动编辑model_info.yaml,后续训练的大模型会自动更新到此文件内,无需再手动编辑) 将$MODEL_NAME替换为模型名称;(如chatglm2-6b) 将$MODEL_DIR替换为基于BASE_DIR的模型相对路径;(如llm/ChatGLM2-6B) ...
## llm_finetune服务,全新部署或历史版本升级 ### 一、环境准备: 1. 代码 > git clone https://github.com/simonlisiyu/llm_finetune.git > > cd llm_finetune > > pip install -r requirements.txt 2. 目录准备 > cd llm_finetune 创建配置目录`mkdir config`,生成配置文件 `touch config/trainer....
Finetune Llama 3.3, Mistral, Phi-4, Qwen 2.5 & Gemma LLMs 2-5x faster with 70% less memory - unslothai/unsloth
Simple LLM Finetuner 🦙 yellow orange gradio app.py false 👻👻👻 This project is effectively dead. Please use one of the following tools instead: https://github.com/hiyouga/LLaMA-Factory https://github.com/unslothai/unsloth