imanjundi

imanjundi's Stars

• meta-llama/llama

  Inference code for Llama models

  Language:Python55.4k5169579.4k

• lm-sys/FastChat

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

  Language:Python36.4k3471.8k4.5k

• tatsu-lab/stanford_alpaca

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

  Language:Python29.3k3392674k

• huggingface/diffusers

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

  Language:Python25k1934k5.2k

• guidance-ai/guidance

  A guidance language for controlling large language models.

  Language:Jupyter Notebook18.6k1175231k

• tloen/alpaca-lora

  Instruct-tune LLaMA on consumer hardware

  Language:Jupyter Notebook18.5k1524682.2k

• stanfordnlp/dspy

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

  Language:Python16.5k1366951.3k

• unslothai/unsloth

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

  Language:Python15.3k997731k

• RUCAIBox/LLMSurvey

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

  Language:Python10k15359784

• artidoro/qlora

  QLoRA: Efficient Finetuning of Quantized LLMs

  Language:Jupyter Notebook9.9k84248814

• microsoft/promptbase

  All things prompt engineering

  Language:Python5.3k5913292

• Instruction-Tuning-with-GPT-4/GPT-4-LLM

  Instruction Tuning with GPT-4

  Language:HTML4.2k4334299

• bigscience-workshop/promptsource

  Toolkit for creating, sharing and using natural language prompts.

  Language:Python2.6k32162346

• huggingface/setfit

  Efficient few-shot learning with Sentence Transformers

  Language:Jupyter Notebook2.1k21304217

• THUDM/AgentBench

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

  Language:Python2.1k29137146

• eric-mitchell/direct-preference-optimization

  Reference implementation for DPO (Direct Preference Optimization)

  Language:Python2k1980162

• THUDM/P-tuning-v2

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

  Language:Python2k2975198

• stanford-crfm/helm

  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 models in Holistic Evaluation of Text-to-Image Models (HEIM) (https://arxiv.org/abs/2311.04287).

  Language:Python1.9k351.1k243

• DigitalPhonetics/IMS-Toucan

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

  Language:Python1.4k21156152

• GaryYufei/AlignLLMHumanSurvey

  Aligning Large Language Models with Human: A Survey

  66127129

• johnsmith0031/alpaca_lora_4bit

  Language:Python5341212284

• HazyResearch/H3

  Language Modeling with the H3 State Space Model

  Language:Assembly509322653

• r-three/t-few

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

  Language:Python42383258

• ezelikman/parsel

  Code for Parsel 🐍 - generate complex programs with language models

  Language:Python40510636

• kongds/Prompt-BERT

  PromptBERT: Improving BERT Sentence Embeddings with Prompts

  Language:Python32943532

• facebookresearch/tart

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

  Language:Python15981211

• symanto-research/few-shot-learning-label-tuning

  A few-shot learning method based on siamese networks.

  Language:Python28413

• yiren-jian/LM-SupCon

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

  Language:Python221

• allenai/adapt-demos

  Lightweight tools for quick and easy LLM demo's

  Language:Python211

• suzyahyah/modeling_belief_alignment_arguments

  Language:Python1110