Tags: #finetuning

A comprehensive framework from ModelScope for efficiently fine-tuning, evaluating, and deploying over 1000 large language models and multimodal large models using advanced techniques.

A production-ready, easy-to-use AI agent framework designed for building, running, and finetuning intelligent agents with transparent and trustworthy capabilities.

A comprehensive guide and collection of recipes for building with the Llama model family, covering inference, fine-tuning, RAG, and end-to-end use cases.

Learn to design, train, and deploy a real-time financial advisor LLM system using a hands-on, three-pipeline approach.

An end-to-end platform for fine-tuning, evaluating, and deploying open-source Large Language Models (LLMs) and Vision Language Models (VLMs).

Provides a collection of Colab notebooks for efficiently fine-tuning large language models using PEFT methods like LoRA and Hugging Face transformers.

A cost-effective solution for fine-tuning ChatGLM-6B using LoRA, enabling personalized large language models.

An open-source implementation for efficiently fine-tuning Alibaba Cloud's Qwen-VL series of multimodal large language models using HuggingFace and Liger-Kernel.

A user-friendly web GUI for various LLMs, enhancing interaction with features like agents, file-based QA, and finetuning.

A comprehensive toolkit for fine-tuning ChatGLM-6B, ChatGLM2-6B, and ChatGLM3-6B models using various methods like Freeze, Lora, P-tuning, and full parameter fine-tuning.