Feature Extraction
Transformers
Safetensors
PyTorch
phorensics
computer-vision
media-forensics
deepfake-detection
physics-based-vision
signal-processing
custom_code
Instructions to use Anuran66/Phorensics-Engine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anuran66/Phorensics-Engine with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Anuran66/Phorensics-Engine", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Anuran66/Phorensics-Engine", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 337 Bytes
03b9592 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"architectures": [
"PhorensicsModel"
],
"auto_map": {
"AutoConfig": "phorensics_model.PhorensicsConfig",
"AutoModel": "phorensics_model.PhorensicsModel"
},
"dtype": "float32",
"max_dim": 600,
"model_type": "phorensics",
"patch_size": 128,
"stride": 64,
"transformers_version": "5.18.0"
}
|