Instructions to use Perriewang/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Perriewang/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Perriewang/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Perriewang/my_awesome_model") model = AutoModelForMaskedLM.from_pretrained("Perriewang/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Perriewang/my_awesome_model: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/Perriewang/my_awesome_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Perriewang/my_awesome_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Perriewang/my_awesome_model/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 20aa8cb833d821cc98700727a44786aa1d0f63813bd96ac64677f2ceae9c02de
- Size of remote file:
- 5.11 kB
- SHA256:
- d1a04871df89faf583b19c9e7ac07a734a6bc4103f0d035e141d1cf75e3024f8
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