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PAIR-code
The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.
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Results: 56
PAIR-code
The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.
openvenues
A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data.
TuringLang
Bayesian inference with probabilistic programming.
bespokelabsai
Synthetic data curation for post-training and structured data extraction
triton-inference-server
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
py-why
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inferen…
deepspeedai
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
ray-project
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
probcomp
A general-purpose probabilistic programming system with programmable inference
mlabonne
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
gunthercox
ChatterBot is a machine learning, conversational dialog engine for creating chat bots
LAION-AI
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
pyro-ppl
Deep universal probabilistic programming with Python and PyTorch