Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!
- evaluation
- evaluation-metrics
- guidebook
- large-language-models
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Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!
Logica is a logic programming language that compiles to SQL. It runs on DuckDB, Google BigQuery, PostgreSQL and SQLite.
《面向开发者的 ChatGPT 提示词工程》非官方版中英双语字幕 Unofficial subtitles of "ChatGPT Prompt Engineering for Developers"
The Classiq Library is the largest collection of quantum algorithms and applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌
Code and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://amzn.to/3JUgR2L
Official implementation for "Automatic Chain of Thought Prompting in Large Language Models" (stay tuned & more will be updated)
[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
Udemy üzerindeki Python kurslarında kullanılan materyaller
OneDiff: An out-of-the-box acceleration library for diffusion models.
Multiple NVIDIA GPUs or Apple Silicon for Large Language Model Inference?
Run any Llama 2 locally with gradio UI on GPU or CPU from anywhere (Linux/Windows/Mac). Use `llama2-wrapper` as your local llama2 backend for Generative Agents/Apps.
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100 days of LLM inference engineering — daily posts, experiments, and visualizations
Python for Finance (O'Reilly)
Natural Gradient Boosting for Probabilistic Prediction
Gallery of OSMnx tutorials, usage examples, and feature demonstrations.
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.
A comprehensive guide to building RAG-based LLM applications for production.
Awesome-pytorch-list 翻译工作进行中......
Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)
Vision utilities for web interaction agents 👀
fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
Notebooks covering mathematical analysis of ZKP building blocks, algorithm implementations of various proof systems, and protocol optimization techniques.
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).