Unsloth
Description
️ 🖼Tool Name:
Unsloth
🔖 Tool Category:
A high-performance AI model training platform, supporting Llama, Mistral, and Gemma models, with GPU and MultiGPU options for acceleration and advanced training.
️ ✏What does this tool offer?
Unsloth allows users to train AI models quickly and efficiently, supporting 4 and 16-bit LoRA, optimizing memory usage, and providing inference acceleration tools on various GPUs.
⭐ What does the tool actually deliver based on user experience?
The experience delivers improved training and inference performance, full support for popular models, flexibility to use one or multiple GPUs, easy UI via Google Colab or Kaggle, and a no-cost free trial.
🤖 Does it include automation?
Yes, the tool supports training automation and inference, automatic memory optimization, and Multi-node and Multi-GPU support for efficient acceleration of large and complex training runs.
💰 Pricing Model:
Unsloth offers three main plans: Free, Professional, and Enterprise, with pay-as-you-go options and customized services for businesses and organizations.
🆓 Free Plan Details:
The free version is open source.
Support for Llama 1, 2, 3, Mistral, and Gemma models.
4 and 16-bit LoRA support.
Single GPU support, MultiGPU under development.
Cost: Completely free, get started via Google Colab or Kaggle.
💳 Paid Plan Details:
Unsloth Pro: 2.5x faster training, 20% lower VRAM consumption, MultiGPU support up to 8 units, cost per use by contacting the team.
Unsloth Enterprise: Up to 30x faster training, 30% increased model accuracy, Multi-node support, full training and client support, cost-per-use with a customized quote.
Support for inference acceleration at twice the speed, support for NVIDIA, Intel, and AMD modules.
🧭 Access Method:
Unsloth can be accessed directly via browser through Google Colab or Kaggle, without the need to download any software, with an easy and flexible user interface for all levels of users.
🔗 Experience Link:
To get started with Unsloth, visit the official website: unsloth.ai and start training on high-performance AI models.