Instructions to use immanuelpeter/MoonViT-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use immanuelpeter/MoonViT-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="immanuelpeter/MoonViT-V2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("immanuelpeter/MoonViT-V2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
MoonViT-V2
This repository packages the Kimi K3 MoonViT-V2 Tower and Projector. It reproduces K3's image path without downloading the full 96-shard, 2.8T-parameter checkpoint. AI4Industry/MoonViT-V2 publishes the Tower alone.
Contents
| File | Tensors | What it holds |
|---|---|---|
model.safetensors |
165 | MoonViT-V2 Tower, bit-identical to AI4Industry/MoonViT-V2 |
projector.safetensors |
3 | Kimi K3 patchmergerv2 |
projector_config.json |
Projector shapes, read from the weights | |
config.json, configuration_moonvit_v2.py, modeling_moonvit_v2.py, image_processing_moonvit_v2.py, preprocessor_config.json |
Vendored from AI4Industry/MoonViT-V2 |
Architecture
| Component | Details |
|---|---|
| Tower | 27 layers, 1024 hidden, 12 heads, 1536 QKV, patch size 14 |
| Token compression | 2x2 pixel shuffle plus temporal pooling, no learned parameters |
| Projector | Linear(4096, 4096) no bias, GELU, Linear(4096, 7168) no bias, RMSNorm(7168) |
Usage
See examples/inference.py for a complete image-to-projected-features
example.
Reproduction
The export script
extracts mm_projector from shard 95 and vision_tower from shard 96 of
moonshotai/Kimi-K3. It preserves the original BF16 weights and verifies all 165 Tower
tensors against AI4Industry/MoonViT-V2 before writing.
Credits
Moonshot AI released the Kimi K3 weights. The modeling and image-processing code comes
unchanged from AI4Industry/MoonViT-V2.
License
Kimi K3 License, the same license as the source model.
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Base model
moonshotai/Kimi-K3