Convert a model to Safetensors and open a PR
Train a model using custom data
Save user inputs to datasets on Hugging Face
Organize and process datasets for AI models
Create a domain-specific dataset project
Organize and invoke AI models with Flow visualization
Upload files to a Hugging Face repository
Create and validate structured metadata for datasets
Convert and PR models to Safetensors
Create a report in BoAmps format
Find and view synthetic data pipelines on Hugging Face
Create a large, deduplicated dataset for LLM pre-training
Curate and manage datasets for AI and machine learning
Convert to Safetensors is a practical tool designed to convert AI models to the Safetensors format, a modern, efficient alternative to older formats like PyTorch's .pt files. Its primary purpose is to simplify model conversion and ** FACILITATE the creation of pull requests (PRs)** for integrating these models into larger projects or libraries. By using this tool, users can ensure their models are compatible with the latest standards in AI model sharing.
pip install convert-to-safetensors to install the package.convert-to-safetensors --input-path /path/to/model --output-path /path/to/output.What is the Safetensors format?
Safetensors is a secure and efficient format for storing and sharing AI models, designed to replace older formats like PyTorch's .pt files. It offers better security and compatibility across different frameworks.
Can I use Convert to Safetensors for non-PyTorch models?
Yes, Convert to Safetensors supports models from various frameworks, including TensorFlow and others, making it a versatile tool for AI practitioners.
Where are the converted models stored?
The converted models are stored in the output directory you specify during the conversion process. Ensure you have write permissions for the target directory.