Quantifying-Surprise-EHRs

? Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

The Web framework for perfectionists with deadlines.

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

Drag & drop UI to build your customized LLM flow

Making large AI models cheaper, faster and more accessible

Build and share delightful machine learning apps, all in Python. ? Star to support our work!

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more