#python #agent #ai #chatglm #fine_tuning #gpt #instruction_tuning #language_model #large_language_models #llama #llama3 #llm #lora #mistral #moe #peft #qlora #quantization #qwen #rlhf #transformers

LLaMA Factory is a tool that makes it easy to fine-tune large language models. It supports many different models like LLaMA, ChatGLM, and Qwen, among others. You can use various training methods such as full-tuning, freeze-tuning, LoRA, and QLoRA, which are efficient and save GPU memory. The tool also includes advanced algorithms and practical tricks to improve performance.

Using LLaMA Factory, you can train models up to 3.7 times faster with better results compared to other methods. It provides a user-friendly interface through Colab, PAI-DSW, or local machines, and even offers a web UI for easier management. The benefit to you is that it simplifies the process of fine-tuning large language models, making it faster and more efficient, which can be very useful for research and development projects.

https://github.com/hiyouga/LLaMA-Factory

#python #deepseek #deepseek_r1 #fine_tuning #finetuning #gemma #gemma2 #llama #llama3 #llm #llms #lora #mistral #phi3 #qlora #unsloth

Using Unsloth.ai, you can finetune AI models like Llama, Mistral, and others up to 2x faster and with 70% less memory. The process is beginner-friendly; you just need to add your dataset, click "Run All" in the provided notebooks, and you'll get a faster, finetuned model that can be exported or uploaded to platforms like Hugging Face. This saves time and resources, making it easier to work with large AI models without needing powerful hardware. Additionally, Unsloth supports various features like 4-bit quantization, long context windows, and integration with tools from Hugging Face, making it a powerful tool for AI model development.

https://github.com/unslothai/unsloth

#jupyter_notebook #chinese_llm #chinese_nlp #finetune #generative_ai #instruct_gpt #instruction_set #llama #llm #lora #open_models #open_source #open_source_models #qlora

AirLLM is a tool that lets you run very large AI models on computers with limited memory by using a smart layer-by-layer loading technique instead of traditional compression methods. You can run a 70-billion-parameter model on just 4GB of GPU memory, or even a 405-billion-parameter model on 8GB, without losing model quality. The benefit is that you can use powerful AI models on affordable hardware without expensive upgrades, and the tool also offers optional compression features that can speed up performance by up to 3 times while maintaining accuracy.

https://github.com/lyogavin/airllm