Instructions to use xiaomoguhzz/VisionEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xiaomoguhzz/VisionEncoder with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xiaomoguhzz/VisionEncoder", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| # 混合 SFT 数据配置(采样版) | |
| # 自动生成 by sample_sft_data.py | |
| # Image: 73,859 条 | |
| # Video: 113,616 条 | |
| # 总计: 187,475 条 | |
| datasets: | |
| # ===== Image ===== | |
| - json_path: /mnt/bn/strategy-mllm-train/common/datasets/image_sft_small_10pct.json | |
| sampling_strategy: all | |
| # ===== Video ===== | |
| - json_path: /mnt/bn/strategy-mllm-train/common/datasets/video_sft_small_10pct.json | |
| sampling_strategy: all | |