转载: 【peft】huggingface大模型加载多个LoRA并随时切换-CSDN博客from peft import PeftModel from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig model_name = "decapoda-resea…
__init__(self, config: T5Config):构造方法与之前的T5模型相似,但额外添加了lm_head,它是一个线性层用于进行语言建模。 forward方法:与之前的T5模型的forward方法相似,但在解码过程中,输出序列的隐藏状态经过lm_head来生成预测的下一个词。 prepare_inputs_for_generation方法:用于生成阶段的输入准备。它根据是否...
ppo_trainer = PPOTrainer(model=model,config=config,train_dataset=train_dataset,tokenizer=tokenizer, )forepoch, batchintqdm(enumerate(ppo_trainer.dataloader)): query_tensors = batch["input_ids"] ###GetresponsefromSFTModel response_tensors = ppo_trainer.generate(query_tensors, **generation_kwargs...
Generation config I know it has just been added so it is normal! But the following are missing (and are pretty intuitive w.r.t our other objects such as configs, processors etc): GenerationConfig.from_pretrained("openai/whisper-tiny.en" ...
config=config, train_dataset=train_dataset, tokenizer=tokenizer, ) for epoch, batch in tqdm(enumerate(ppo_trainer.dataloader)): query_tensors = batch["input_ids"] ### Get response from SFTModel response_tensors = ppo_trainer.generate(query_tensors, **generation_kwargs) batch...
首先定义了一个类,BertConfig,这个类包含了所有模型所需要的配置参数,比如hidden_size,number_hidden_...
PRETRAINED_CONFIG_ARCHIVE_MAP', 'ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST', 'ERNIE_PRETRAINED_CONFIG...
Feature request 👋 The request is for a way to pass a GenerationConfig to a Seq2SeqTrainer (through Seq2SeqTrainingArguments). Motivation ATOW, Seq2SeqTrainer only supports a few arguments for generation: max_length / max_new_tokens, num_...
一个完整的transformer模型主要包含三部分:Config、Tokenizer、Model。 Config 用于配置模型的名称、最终输出的样式、隐藏层宽度和深度、激活函数的类别等。 示例: {"architectures":["BertForMaskedLM"],"attention_probs_dropout_prob":0.1,"gradient_checkpointing":false,"hidden_act":"gelu","hidden_dropout_prob...
我们将使用最近在由 Tim Dettmers 等人的发表的论文“QLoRA: Quantization-aware Low-Rank Adapter Tuning for Language Generation”中介绍的方法。QLoRA 是一种新的技术,用于在微调期间减少大型语言模型的内存占用,且并不会降低性能。QLoRA 的 TL;DR; 是这样工作的: ...