Convert and PR models to Safetensors
Search narrators and view network connections
Manage and label your datasets
Create datasets with FAQs and SFT prompts
A collection of parsers for LLM benchmark datasets
Build datasets and workflows using AI models
Manage and orchestrate AI workflows and datasets
Train a model using custom data
Support by Parquet, CSV, Jsonl, XLS
Label data efficiently with ease
Organize and process datasets using AI
Validate JSONL format for fine-tuning
Upload files to a Hugging Face repository
Convert to Safetensors is a tool designed to convert and process models into the Safetensors format. Safetensors are a modern alternative to traditional tensor formats, offering improved memory efficiency and security. This tool simplifies the process of converting models, making it accessible for users working with AI and machine learning applications.
• Efficient Conversion: Quickly convert models to Safetensors format with minimal overhead.
• Compatibility: Works seamlessly with popular AI frameworks and libraries.
• Data Integrity: Ensures that the converted models maintain their original functionality and accuracy.
• Scalability: Handles large-scale models efficiently, making it suitable for enterprise-level applications.
• User-Friendly: Designed with an intuitive interface for ease of use.
What is the advantage of using Safetensors over other formats?
Safetensors offers better memory safety and faster loading times compared to traditional formats like PyTorch (.pt) or TensorFlow (.ckpt).
Can I convert models from any framework using this tool?
Yes, Convert to Safetensors supports models from multiple frameworks, including PyTorch, TensorFlow, and others.
How do I handle large models during conversion?
Large models can be converted in chunks or using distributed processing to manage memory constraints effectively.