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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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81–96 / 122
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Results: 122
PAIR-code
The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.
NVIDIA
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, t…
SeldonIO
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
MAIF
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
promptslab
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest re…
TencentCloudADP
A simple yet powerful agent framework that delivers with open-source models
NVIDIA
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
AnotiaWang
(Supports DeepSeek R1) An AI-powered research assistant that performs iterative, deep research on any topic by combining search engines, web scraping, and large language…
Trusted-AI
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
WenjieDu
A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific an…
qualcomm
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
huggingface
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
fairlearn
A Python package to assess and improve fairness of machine learning models.
aws
A library for training and deploying machine learning models on Amazon SageMaker
superlinked
Open-source inference server and production cluster for all the models your agent needs.
uber
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.