trainer = SFTTrainer( model=model, train_dataset=dataset, peft_config=peft_config, dataset_text_field="text", max_seq_length=max_seq_length, tokenizer=tokenizer, args=training_arguments, ) 8)在微调的时候,对LN层使用float 32训练更稳定 for name, module in trainer.model.named_modules(): if "...
tokenizer.model_max_length= 512 选择量化参数 from transformers import BitsAndBytesConfig bnb_config = BitsAndBytesConfig( load_in_4bit=True, bnb_4bit_use_double_quant=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=torch.bfloat16 ) 加载模型 from transformers import AutoModelForCaus...
disable_tqdm=disable_tqdm, report_to="tensorboard", seed=42)# Create the trainertrainer = SFTTrainer( model=model, train_dataset=dataset, peft_config=peft_config, max_seq_length=max_seq_length, tokenizer=tokenizer, packing=packing, formatting_func=format_instruction, ...
model_name_or_path, model_max_length=2048, padding_side="right", use_fast=False) tokenizer.pad_token = tokenizer.eos_token 接着,设置pyreft配置,然后使用pyreft.get_reft_model()方法准备好模型。 # get reft model reft_config = pyreft.ReftConfig(representations={ "layer": 8, "component":...
LlamaTokenizerFast(name_or_path='NousResearch/Llama-2-7b-hf', vocab_size=32000, model_max_length=1000000000000000019884624838656, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': '<unk>', 'pad_token': '<...
在LLM的应用中，有一个非常重要的参数，叫做LLM支持的上下文长度(max context length)。更长的上下文长度...
pipeline_task=pipeline("text_generation",model='llama_7b',max_length=20)pipeline_result=pipeline_task("I love Beijing, because",top_k=3)print(pipeline_result) 1. 2. 3. 4. - 当我输入提示词: text_generation_text':I love Beijing,because ...
Please, answer in pirate-speak."},]outputs = pipe( messages, max_new_tokens=256, do_sample=False,)assistant_response = outputs[]["generated_text"][-1]["content"]print(assistant_response)# Arrrr, me hearty! Yer lookin' fer a bit o' information about meself, eh? Alright then...
--model_max_length 2048 --gradient_checkpointing True --lazy_preprocess True --bf16 True --tf32 True --report_to "none" """ 微调脚本 微调使用 torchrun + DeepSpeed 进行分布式训练 %%writefile./src/ds-train-dist.sh#!/bin/bashCURRENT_HOST="${SM_CURRENT_HOST}"IFS=','read-ra hosts_ar...
pipeline_task= pipeline("text_generation", model='llama_7b', max_length=20) pipeline_result= pipeline_task("I love Beijing, because", top_k=3) print(pipeline_result) - 当我输入提示词: text_generation_text': I love Beijing, because ...