Image Feature Extraction
Transformers
Safetensors
monkeyocrv2_vitae_encoder
feature-extraction
custom_code
Instructions to use zenosai/MonkeyOCRv2-AS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenosai/MonkeyOCRv2-AS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="zenosai/MonkeyOCRv2-AS", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zenosai/MonkeyOCRv2-AS", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 483 Bytes
bb5b74a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"auto_map": {
"AutoProcessor": "configuration_monkeyocrv2_vitae.MonkeyOCRv2ViTAEProcessor"
},
"min_pixels": 4096,
"max_pixels": 11289600,
"patch_size": 32,
"temporal_patch_size": 1,
"merge_size": 1,
"encoder_stride": 32,
"image_mean": [
0.48145466,
0.4578275,
0.40821073
],
"image_std": [
0.26862954,
0.26130258,
0.27577711
],
"image_processor_type": "Qwen2VLImageProcessor",
"processor_class": "MonkeyOCRv2ViTAEProcessor"
}
|