wxjdufe's Stars
openai/lm-human-preferences
Code for the paper Fine-Tuning Language Models from Human Preferences
tonyzhaozh/few-shot-learning
Few-shot Learning of GPT-3
jalammar/deep-learning
Repo for the Deep Learning Nanodegree Foundations program.
tensorflow/nmt
TensorFlow Neural Machine Translation Tutorial
shmsw25/Channel-LM-Prompting
An original implementation of "Noisy Channel Language Model Prompting for Few-Shot Text Classification"
jalammar/jalammar.github.io
Build a Jekyll blog in minutes, without touching the command line.
jalammar/ecco
Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).
harvardnlp/annotated-transformer
An annotated implementation of the Transformer paper.
intel/auto-round
Advanced Quantization Algorithm for LLMs. This is official implementation of "Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs"
INK-USC/CrossFit
Code for paper "CrossFit :weight_lifting:: A Few-shot Learning Challenge for Cross-task Generalization in NLP" (https://arxiv.org/abs/2104.08835)
cole-maclean/MAI-CI
openai/automated-interpretability
openai/gpt-3
GPT-3: Language Models are Few-Shot Learners
salesforce/ctrl
Conditional Transformer Language Model for Controllable Generation
fajieyuan/SIGIR2020_peterrec
Universal User Representation Pre-training for Cross-domain Recommendation and User Profiling
openai/summarize-from-feedback
Code for "Learning to summarize from human feedback"
rudinger/winogender-schemas
Data for evaluating gender bias in coreference resolution systems.
huggingface/datasets
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
rowanz/grover
Code for Defending Against Neural Fake News, https://rowanzellers.com/grover/
declare-lab/instruct-eval
This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.
anthropics/hh-rlhf
Human preference data for "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback"
zwq2018/Data-Copilot
Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow
google/BIG-bench
Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models
nomic-ai/gpt4all
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
declare-lab/flan-alpaca
This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.
Instruction-Tuning-with-GPT-4/GPT-4-LLM
Instruction Tuning with GPT-4
yizhongw/self-instruct
Aligning pretrained language models with instruction data generated by themselves.
declare-lab/flacuna
Flacuna was developed by fine-tuning Vicuna on Flan-mini, a comprehensive instruction collection encompassing various tasks. Vicuna is already an excellent writing assistant, and the intention behind Flacuna was to enhance Vicuna's problem-solving capabilities. To achieve this, we curated a dedicated instruction dataset called Flan-mini.
THUDM/CogVLM
a state-of-the-art-level open visual language model | 多模态预训练模型
google-research/FLAN