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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 425 Bytes
05695ac | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # 混合 SFT 数据配置(采样版)
# 自动生成 by sample_sft_data.py
# Image: 738,590 条
# Video: 800,001 条
# 总计: 1,538,591 条
datasets:
# ===== Image =====
- json_path: /mnt/bn/strategy-mllm-train/common/datasets/image_sft_full_v800k.json
sampling_strategy: all
# ===== Video =====
- json_path: /mnt/bn/strategy-mllm-train/common/datasets/video_sft_full_v800k.json
sampling_strategy: all
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