Instructions to use wangyh6/BlazeFace-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wangyh6/BlazeFace-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="wangyh6/BlazeFace-v2", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("wangyh6/BlazeFace-v2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "BlazeFace" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "DCU_CONFIG.DcuConfig", | |
| "AutoModelForImageClassification": "DCU_MODEL.BlazeFace" | |
| }, | |
| "model_type": "blazeface", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.42.4" | |
| } | |