Instructions to use clicknext/phayathaibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clicknext/phayathaibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="clicknext/phayathaibert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("clicknext/phayathaibert") model = AutoModelForMaskedLM.from_pretrained("clicknext/phayathaibert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf0bebaa1a25f8953519669edcfc895e798def4ab3ed9f3b51e86224a6987be7
- Size of remote file:
- 17.4 MB
- SHA256:
- d8c7c1ec376502023be87abc9440ef5e643f70e569225799ad2d261c488c1083
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