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MiniMind-V

Train a 26M-parameter visual multimodal VLM from scratch in just 1 hour, suitable for deep learning enthusiasts.

Introduction

MiniMind-V

MiniMind-V is an innovative visual language model (VLM) that allows you to train a 26M-parameter model from scratch in just 1 hour using a single NVIDIA 3090 GPU. This project aims to provide a minimal and effective implementation of VLMs, emphasizing accessibility for individuals with basic hardware setups.

Key Features:
  • Quick Training: Achieve training completion in just one hour with low resource costs.
  • Multimodal Input: Integrate visual data alongside textual input for enhanced model capabilities.
  • Step-by-Step Guide: Detailed documentation available for setting up the environment, downloading models, and running training.
Benefits:
  • Cost-Effective: Total operational cost as low as 1.3 RMB for GPU server rental.
  • Open Source: Freely accessible code that encourages contributions and enhancements.
  • User Friendly: Comprehensive instructions that cater to beginners in the field of deep learning and model training.
Highlights:
  • Efficient framework that supports both pretraining and supervised fine-tuning (SFT) processes.
  • Compatibility with existing models like CLIP for the visual encoder, making integration seamless.
  • Designed for community contributions—users are encouraged to report issues and suggest improvements.

Join the MiniMind-V project to explore the fascinating world of visual language models and contribute to its development!

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