python3 trl_finetune.py -m NousResearch/Llama-2-7b-hf --block_size 1024 --eval_steps 10 --save_steps 20 --log_steps 10 -tf mixtral/train.csv -vf mixtral/val.csv -b 2 -lr 1e-4 --lora_alpha 16 --lora_r 64 -e 1 --gradient_accumulation_steps 4 --pad_token_id=18610 --...
微调的结果其实并不是实际的Llama 2模型,而是适配到模型上的一个adapter(Axolotl默认使用qlora来生成Llama模型),所以最终,adapter的大小仅为320MB。 使用Axolotl进行推理也非常简单:我只需要下载这个模型,然后启动Axolotl推理命令: # download from fine tuned repo git lfs install git clone https://huggingface.co/...
将数据集重命名为 alpaca_data.json，并放置于 llama-recipes/ft_datasets 下。其次，下载 Hugging Face 格式的模型权重。在下载前，请先在 Hugging Face 申请 LLaMA-2 权重并获取 Access Token。使用 huggingface_hub.snapshot_download 或 git 下载模型至本地。最后，使用 llama-recipes 内置的 alpaca...
clone llama-recipes repository tied with llama2-tutorial, here is the directory structure, no matter where you put your data, but needs to be specified in your dataset.py code fine tuning run the following code under llama2-tutorial folder. python -m llama_recipes.finetuning \--use_peft \...
Hello, I am experiencing the following error: You're using a LlamaTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pa...
Learn to fine-tune Llama2 more efficiently with recently enabled Low-Rank Adaptations (LoRA) on Gaudi2 processors
# 2.使用huggingface数据 dataset_path = "lamini/lamini_docs" use_hf = True 1. 2. 3. 4. 5. 6. 7. 8. 2.3 设置模型、训练配置、分词器 model_name = "EleutherAI/pythia-70m" training_config = { "model": { "pretrained_name": model_name, ...
"help": "Where do you want to store the pretrained models downloaded from huggingface.co"}, ) lora_r: Optional[int] = field(default=16) lora_alpha: Optional[int] = field(default=32) target_modules: Optional[str] = field( ...
I have download the projector from https://huggingface.co/liuhaotian/llava-pretrain-llama-2-7b-chat to ./checkpoints/llava-pretrain-llama-2-7b-chat. According to the guide in https://github.com/haotian-liu/LLaVA/blob/main/scripts/v1_5/finetune.sh and https://github.com/haotian-liu...
value: meta-llama/Llama-2-13b-hf - name: HUGGING_FACE_HUB_TOKEN value: <your-hugging-face-token> - name: LD_LIBRARY_PATH value: /usr/local/nvidia/lib:/usr/local/nvidia/lib64:/opt/conda/lib - name: OCI__METRICS_NAMESPACE value: finetune_llama2_13b_hf_peft_lora</your-hugging-face...