77 lines
2.6 KiB
Markdown
77 lines
2.6 KiB
Markdown
# MiniMind-V Documentation Migration Summary
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## Changes Made
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### 1. Configuration Files
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- **mkdocs.yml**: Updated site name, description, and URL from "MiniMind" to "MiniMind-V"
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### 2. Images
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- **Removed**: All old MiniMind LLM-related images
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- **Added**: MiniMind-V VLM-specific images from `/images/`:
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- logo.png
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- minimind2-v.gif
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- VLM-structure.png
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- VLM-structure-moe.png
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- llava-structure.png
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- minimind-v-input.png
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- pretrain_loss.png
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- sft_loss.png
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### 3. Documentation Files (All in English)
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#### index.md
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- Changed from LLM introduction to VLM introduction
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- Updated model list to show MiniMind-V variants
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- Added VLM-specific concepts and architecture
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- Updated related links to minimind-v repository
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#### quickstart.md
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- Updated from LLM quick start to VLM quick start
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- Added CLIP model download instructions
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- Changed evaluation script from `eval_model.py` to `eval_vlm.py`
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- Updated model architecture section with Visual Encoder details
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- Added image-text dialogue examples
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#### training.md
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- Changed from LLM training to VLM training
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- Added VLM dataset formats (pretrain_vlm_data, sft_vlm_data, sft_vlm_data_multi)
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- Updated training scripts to `train_pretrain_vlm.py` and `train_sft_vlm.py`
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- Added Visual Encoder and Projection layer explanations
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- Updated training pipeline with VLM-specific steps
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- Added multi-image fine-tuning section
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#### README.md
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- Updated project description to MiniMind-V
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- Changed documentation URL to minimind-v.readthedocs.io
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- Updated GitHub links to minimind-v repository
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## Key Differences: MiniMind vs MiniMind-V
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| Aspect | MiniMind (LLM) | MiniMind-V (VLM) |
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|--------|----------------|------------------|
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| Type | Language Model | Vision-Language Model |
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| Input | Text only | Text + Images |
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| Components | Transformer Decoder | Transformer Decoder + Visual Encoder + Projection |
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| Training Data | Text (pretrain.jsonl, sft.jsonl) | Text + Images (pretrain_vlm_data, sft_vlm_data) |
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| Eval Script | eval_model.py | eval_vlm.py |
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| Training Scripts | train_pretrain.py, train_full_sft.py | train_pretrain_vlm.py, train_sft_vlm.py |
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| Model Weights | *.pth (LLM only) | *.pth (LLM + Visual components) |
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## Verification
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All documentation now correctly references:
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- ✅ MiniMind-V project name
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- ✅ VLM-specific architecture diagrams
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- ✅ Vision-language training pipeline
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- ✅ Correct repository URLs (minimind-v)
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- ✅ VLM evaluation and inference scripts
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- ✅ Image-text dataset formats
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- ✅ English language throughout
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## Next Steps
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1. Deploy to ReadTheDocs at minimind-v.readthedocs.io
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2. Ensure .readthedocs.yaml is properly configured
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3. Test local build with `mkdocs serve`
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4. Verify all image links work correctly
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