jtan189
Follow
Stars
A framework for few-shot evaluation of language models.
❗ This is a read-only mirror of the CRAN R package repository. nlme — Linear and Nonlinear Mixed Effects Models. Homepage: https://svn.r-project.org/R-packages/trunk/nlme/ Report bugs for this pack…
Mixed-effects models in R using S4 classes and methods with RcppEigen
Simple, safe way to store and distribute tensors
The OpenAPI Specification Repository
🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Data validation using Python type hints
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.
A guidance language for controlling large language models.
LlamaIndex is the leading framework for building LLM-powered agents over your data.
🦜🔗 Build context-aware reasoning applications
a python script to send weather info to me every day
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
A curated list of NLP resources focused on Transformer networks, attention mechanism, GPT, BERT, ChatGPT, LLMs, and transfer learning.
Deep Learning / Machine Learning reading list - mainly related to NLP
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
macOS development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapRed…
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
Book about interpretable machine learning
Check a password in haveibeenpwned using pure JavaScript