In a single-server configuration with a single GPU card, the time taken to fine-tune Llama 2 7B ranges from 5.35 hours with one Intel® Data Center GPU Max 1100 to 2.4 hours with one Intel® Data Center GPU Max 1550. When the configuration is scaled up to 8 GPUs, the...
QLora(Int4) + split model python3 trl_finetune.py -m NousResearch/Llama-2-7b-hf --block_size 1024 --eval_steps 2 --save_steps 20 --log_steps 2 -tf mixtral/train.csv -vf mixtral/val.csv -b 2 -lr 1e-4 --lora_alpha 16 --lora_r 64 -e 1 --gradient_accumulation_steps 2...
Part 1: Fine-tune a Llama2-7b model using PEFT We are going to use the recently introduced method in the paper QLoRA: Quantization-aware Low-Rank Adapter Tuning for Language Generation by Tim Dettmers et al. QLoRA is a new technique to reduce the memory ...
我将在单个GPU上使用Qlora方法对Llama2-chat 7B参数模型进行实验。 看看我之前用原始模型生成的宋词: 再对比一下经过fine-tune后,我生成的唐诗。可以看出,文字之间的逻辑关系有了显著的提升: 目前,主流的fine-tune方法主要分为全参数训练(Full Parameter)和参数高效训练(Parameter Efficient Tuning)。全参数训练就是...
Learn to fine-tune Llama2 more efficiently with recently enabled Low-Rank Adaptations (LoRA) on Gaudi2 processors
1.从零创造大模型，成本高：对大部分公司而言，也很难负担从零开始训练一个大模型的成本。meta最近开源的 llama3.1 405B模型，24000张H100集群，训练54天。但在开源模型之上进行微调，使用一些量化（减少精度）微调方式，可以大大降低门槛，还可以得到不错的效果。2.降低每次请求的成本：一般而言，相同的性能表现，...
Fine-tune the recent Llama-2-7b model on a single GPU and turn it into a chatbot I will leverage PEFT library from Hugging Face ecosystem, as well as QLoRA for more memory efficient finetuning. - DavidLanz/Llama2-Fine-Tuning-using-QLora
LoraConfig, PeftModel, get_peft_model, get_peft_model_state_dict, prepare_model_for_int8_training, prepare_model_for_kbit_training, set_peft_model_state_dict, ) import transformers from transformers.trainer_utils import PREFIX_CHECKPOINT_DIR ...
1.从零创造大模型,成本高:对大部分公司而言,也很难负担从零开始训练一个大模型的成本。meta最近开源的 llama3.1 405B模型,24000张H100集群,训练54天。但在开源模型之上进行微调,使用一些量化(减少精度)微调方式,可以大大降低门槛,还可以得到不错的效果。
play_arrow 6m 13s · GPU T4 x2 Language Python Table of Contents OverviewPreparing the datasetLoading the model and tokenizerQuantize a modelFreeze Original WeightsLoRA configTraining argumentsSave the adapter and the modelInferencingMerging the adapter with modelCredits License This Notebook has been...