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ZJUICI
- Hangzhou, Zhejiang, China
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🪢 Open source LLM engineering platform: Observability, metrics, evals, prompt management, playground, datasets. Integrates with LlamaIndex, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
A framework for the evaluation of autoregressive code generation language models.
Official JAX implementation of Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Official PyTorch implementation of Learning to (Learn at Test Time): RNNs with Expressive Hidden States
The blessed GitHub Action, for publishing your 📦 distribution files to PyPI: https://github.com/marketplace/actions/pypi-publish
LiveBench: A Challenging, Contamination-Free LLM Benchmark
Dynamically provisioning persistent local storage with Kubernetes
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
Code for the paper titled "Instruction Tuning With Loss Over Instructions"
Parameter-Efficient Sparsity Crafting From Dense to Mixture-of-Experts for Instruction Tuning on General Tasks
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
LangStream. Event-Driven Developer Platform for Building and Running LLM AI Apps. Powered by Kubernetes and Kafka.
Offical code for the CVPR 2024 Paper: Separating the "Chirp" from the "Chat": Self-supervised Visual Grounding of Sound and Language
OpenCompass is an LLM evaluation platform, supporting a wide range of models (Llama3, Mistral, InternLM2,GPT-4,LLaMa2, Qwen,GLM, Claude, etc) over 100+ datasets.
Video+code lecture on building nanoGPT from scratch
FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.
OpenGFW is a flexible, easy-to-use, open source implementation of GFW (Great Firewall of China) on Linux
Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs
Freeing data processing from scripting madness by providing a set of platform-agnostic customizable pipeline processing blocks.
Human preference data for "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback"