python-m llama_recipes.finetuning --use_peft --peft_method lora --quantization --model_name ../llama/models_hf/7B --output_dir ../llama/PEFT/model # multiple GPUs torchrun --nnodes 1 --nproc_per_node 1 examples/finetuning.py --enable_fsdp --use_peft --peft_method lora --model_...
llama-factory fine-tuning 4 (mixtral fine-tuning) introduction fine-tuning command mistral click to view the code CUDA_VISIBLE_DEVICES=1nohup python src/train_bash.py \--stage sft \--do_train \--model_name_or_path mistralai/Mistral-7B-v0.1 \--dataset alpaca_med_cqa_en \--template mis...
finetuning llama 流星412 发消息 死去的毛囊突然开始复苏了 -百兽凯多- 接下来播放 自动连播 llama03_RoPE 流星412 5 0 llama06-tokenizer 流星412 1 0 llama10_llamafactory-lora 流星412 17 0 llama04_GQA-KVcache 流星412 3 0 llama02_rms-swiglu 流星412 4 0 ...
View Active Events Khushdeep Bansal·6mo ago· 523 views arrow_drop_up5 Copy & Edit24 more_vert Copied from Khushdeep Bansal (+16,-30) Runtime play_arrow 6h 48m 49s · GPU T4 x2 Language Python Competition Notebook ARC Prize 2024...
TC-Llama 2 addresses these limitations by utilizing the advanced generalization capabilities of LLMs, specifically adapting them to this intricate domain. Our model, based on the open-source LLM framework, Llama 2, is customized through instruction tuning using bilingual Korean-English datasets. Our ...
对llama3进行全参微调、lora微调以及qlora微调。. Contribute to taishan1994/Llama3.1-Finetuning development by creating an account on GitHub.
llama2-lora-ft.ipynb: This notebook provides a sample workflow for fine-tuning the Llama 2 parameter base model for extractive Question-Answering on the SQuAD dataset using Low-Rank Adaptation Fine-tuning (LoRA), a popular parameter-efficient fine-tuning method. llama2-ptuning.ipynb: This note...
- Llama 3.2 1B和3B型号与Unsloth兼容,使用少于4GB的VRAM,并且比HF+FA2快2倍。 - 推理速度也比vLLM / torch.compile快2倍,对于单个GPU而言快10-15%。 - 3B微调需要大约7GB的空间。 - 4位预量化模型可以节省1GB的VRAM碎片,并且下载速度快4倍。 - VLM支持即将推出。 - Kaggle提供每周30小时的免费T4 GPU...
🟢使用多个强大的模型和工具: 1️⃣Google-BERT:用于高效的文本分块 2️⃣LLaMA 3.1 70B:生成高质量的训练数据集 3️⃣LLaMA 3.1 8B:作为我们微调的目标模型 4️⃣Axolotl:一个简单易用的开源微调框架 🟢视频内容包括: 1️⃣文本分块的重要性及其在AI训练中的作用 2️⃣使用Google-BERT...
python -m llama_recipes.finetuning \--use_peft \--peft_method lora \--quantization \--model_name ./llama/models_hf/7B \--dataset custom_dataset \--custom_dataset.file"dataset.py:get_preprocessed_medical"\--output_dir ../llama/fine-tuning/medical \--batch_size_training1\--num_epochs3...