Instructions to use OpenFace-CQUPT/Human_LLaVA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenFace-CQUPT/Human_LLaVA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="OpenFace-CQUPT/Human_LLaVA")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("OpenFace-CQUPT/Human_LLaVA") model = AutoModelForImageTextToText.from_pretrained("OpenFace-CQUPT/Human_LLaVA") - Notebooks
- Google Colab
- Kaggle
File size: 393 Bytes
babae27 | 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 | {
"do_convert_rgb": null,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "SiglipImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"processor_class": "LlavaProcessor",
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 384,
"width": 384
}
}
|