Image Feature Extraction
Transformers
Safetensors
page
feature-extraction
gaze-estimation
gaze-target-estimation
dinov3
custom_code
Instructions to use Octopus1/page-vithplus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Octopus1/page-vithplus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="Octopus1/page-vithplus", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Octopus1/page-vithplus", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 352 Bytes
26634fe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"image_processor_type": "PaGEImageProcessor",
"auto_map": {
"AutoImageProcessor": "Octopus1/PaGE--modeling_page.PaGEImageProcessor"
},
"scene_size": [
512,
512
],
"head_size": [
256,
256
],
"image_mean": [
0.485,
0.456,
0.406
],
"image_std": [
0.229,
0.224,
0.225
],
"resample": 2
} |