Machine learning file extensions
Model and training-artifact formats used in machine learning and data science workflows.
Total extensions in this category: 4
Extensions in Machine learning
Explore the most searched extensions in this category.
- .safetensors
SafeTensors tensor checkpoint format
.safetensors stores machine-learning tensor weights in a simple binary container with a small JSON header and raw tensor bytes. It is commonly used for sharing and loading model checkpoints (especially in the Hugging Face ecosystem) with an emphasis on safer, validation-friendly loading.
- .onnx
ONNX (Open Neural Network Exchange) model
.onnx is a serialized machine-learning model file in the Open Neural Network Exchange (ONNX) format, used to move models between tools and run inference in different environments. It’s commonly loaded by ONNX Runtime and other ONNX-capable ML software rather than “opened” like a document.
- .gguf
GGUF (GGML Universal Format) model file
.gguf is a binary file format used to store machine-learning models (tensors plus metadata), commonly for running LLMs with GGUF-capable local tools and runtimes (llama.cpp is a well-known example). It is designed for fast saving/loading and is often used to distribute quantized models for inference.
- .ml20
Machine Learning Model Format 2020
.ml20 files are used for storing machine learning models, typically created by specific machine learning frameworks.