Transformers
Safetensors
facesmultitasknet
multitask-learning
efficientnet
computer-vision
Generated from Trainer
Instructions to use thethinkmachine/EfficientNetV1-B4-FacesMTL-EXP1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thethinkmachine/EfficientNetV1-B4-FacesMTL-EXP1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import FacesMultiNet model = FacesMultiNet.from_pretrained("thethinkmachine/EfficientNetV1-B4-FacesMTL-EXP1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from thethinkmachine/EfficientNetV1-B4-FacesMTL-EXP1: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/thethinkmachine/EfficientNetV1-B4-FacesMTL-EXP1/resolve/main/training_args.bin
- Command line
-
hf download hf://thethinkmachine/EfficientNetV1-B4-FacesMTL-EXP1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/thethinkmachine/EfficientNetV1-B4-FacesMTL-EXP1/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- e1c3a6dea0abca1a47a8d5f8d997a35912ecde81b96332c166672679c0e5667b
- Size of remote file:
- 5.84 kB
- SHA256:
- d8176b419aea94692ebfc93eb33aa04f908998367c773c46f9c1cccd5cb72178
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