TransformerEngine
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…
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Results: 49
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…
NVIDIA
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
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.
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.
shankarpandala
Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning
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
uber
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
meta-pytorch
Training PyTorch models with differential privacy
kyegomez
Implementation of "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch
Trusted-AI
Interpretability and explainability of data and machine learning models