📖NLP
An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
The code and data for "StructGPT: A general framework for Large Language Model to Reason on Structured Data"
Code and documents of LongLoRA and LongAlpaca (ICLR 2024 Oral)
A series of large language models developed by Baichuan Intelligent Technology
BELLE: Be Everyone's Large Language model Engine（开源中文对话大模型）
An Open-source Toolkit for LLM Development
Fine-tuning ChatGLM-6B with PEFT | 基于 PEFT 的高效 ChatGLM 微调
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
Instruct-tune LLaMA on consumer hardware
🦜🔗 Build context-aware reasoning applications
OpenChat: Advancing Open-source Language Models with Imperfect Data
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Multi-stage Encoder-based Supervised with-clustering (MESc) classification framework
[ICML 2024] TrustLLM: Trustworthiness in Large Language Models
[EMNLP'23, ACL'24] To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.
基于ChatGLM-6B、ChatGLM2-6B、ChatGLM3-6B模型，进行下游具体任务微调，涉及Freeze、Lora、P-tuning、全参微调等
Codes for our paper "RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation"
A simple and efficient Mamba implementation in pure PyTorch and MLX.
A framework for prompt tuning using Intent-based Prompt Calibration
Turning a CLIP Model into a Scene Text Detector (CVPR2023) | Turning a CLIP Model into a Scene Text Spotter (TPAMI)
Public repo for the NeurIPS 2023 paper "Unlimiformer: Long-Range Transformers with Unlimited Length Input"
Official implementation for the paper *Narrowing the Gap between Supervised and Unsupervised Sentence Representation Learning with Large Language Model*
MTEB: Massive Text Embedding Benchmark
[AAAI 2024] DenoSent: A Denoising Objective for Self-Supervised Sentence Representation Learning
[EMNLP 2021] SimCSE: Simple Contrastive Learning of Sentence Embeddings https://arxiv.org/abs/2104.08821