Aligning Large Language Models with Human: A Survey

An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.

All things prompt engineering

Code for Parsel 🐍 - generate complex programs with language models

DSPy: The framework for programming—not prompting—foundation models

Finetune Llama 3.1, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

Reference implementation for DPO (Direct Preference Optimization)

QLoRA: Efficient Finetuning of Quantized LLMs

The official GitHub page for the survey paper "A Survey of Large Language Models".

A guidance language for controlling large language models.

A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)

Code and documentation to train Stanford's Alpaca models, and generate the data.

Multilingual and Controllable Text-to-Speech Toolkit of the Speech and Language Technologies Group at the University of Stuttgart.

Instruction Tuning with GPT-4

Instruct-tune LLaMA on consumer hardware

Inference code for Llama models

Code and model release for the paper "Task-aware Retrieval with Instructions" by Asai et al.

Language Modeling with the H3 State Space Model

Holistic Evaluation of Language Models (HELM), a framework to increase the transparency of language models (https://arxiv.org/abs/2211.09110). This framework is also used to evaluate text-to-image …

An optimized deep prompt tuning strategy comparable to fine-tuning across scales and tasks

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

Toolkit for creating, sharing and using natural language prompts.

Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"

Efficient few-shot learning with Sentence Transformers

[NAACL 2022] Contrastive Learning for Prompt-based Few-shot Language Learners

A few-shot learning method based on siamese networks.

PromptBERT: Improving BERT Sentence Embeddings with Prompts