Instructions to use BigSalmon/GoodMaskResults with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/GoodMaskResults with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigSalmon/GoodMaskResults")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/GoodMaskResults") model = AutoModelForMaskedLM.from_pretrained("BigSalmon/GoodMaskResults", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BigSalmon/GoodMaskResults: direct link, hf CLI and curl.
- Browser
- Download file 2.67 kB
-
https://huggingface.co/BigSalmon/GoodMaskResults/resolve/main/training_args.bin
- Command line
-
hf download hf://BigSalmon/GoodMaskResults/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BigSalmon/GoodMaskResults/resolve/main/training_args.bin
2.67 kB
- Xet hash:
- 7fa1530d0a56b64c4a3c5e6ed8d25eab080b4f1d7ec5f4aa1df61940a0fe8d00
- Size of remote file:
- 2.67 kB
- SHA256:
- 7ccc7a08adc52aeba6fcc8db5047f3104f202dfa8d99ede4ab26fc050b00ce35
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