Unify Efficient Fine-Tuning of 100+ LLMs
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Updated
Jun 11, 2024 - Python
Unify Efficient Fine-Tuning of 100+ LLMs
An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)
Discrete Bayesian optimization with LLMs, PEFT finetuning methods, and the Laplace approximation.
a bro who codes with you
SORSA: Singular Value and Orthogonal Regularized Singular Vector Adaptation of Large Language Models
Implementation for the different ML tasks on Kaggle platform with GPUs.
Low Tensor Rank adaptation of large language models
PEFT is a wonderful tool that enables training a very large model in a low resource environment. Quantization and PEFT will enable widespread adoption of LLM.
Speech, Language, Audio, Music Processing with Large Language Model
Firefly: 大模型训练工具,支持训练Qwen2、Yi1.5、Phi-3、Llama3、Gemma、MiniCPM、Yi、Deepseek、Orion、Xverse、Mixtral-8x7B、Zephyr、Mistral、Baichuan2、Llma2、Llama、Qwen、Baichuan、ChatGLM2、InternLM、Ziya2、Vicuna、Bloom等大模型
Finetuning coding LLM OpenCodeInterpreter-DS-6.7B for Text-to-SQL Code Generation on a Single A100 GPU in PyTorch.
This repository is dedicated to small projects and some theoretical material that I used to get into NLP and LLM in a practical and efficient way.
MindSpore online courses: Step into LLM
This is the official repository for the paper "Flora: Low-Rank Adapters Are Secretly Gradient Compressors" in ICML 2024.
[ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
High Quality Image Generation Model - Comes Under NGC Models @prithivmlmods
Fine Tuning pegasus and flan-t5 pre-trained language model on dialogsum datasets for conversation summarization to to optimize context window in RAG-LLMs
🚂 Fine tuning large language models
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