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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f587a72b4e9c8a07f6ab08123b3da7e03aefe6f03efc63ba82b93d7eca12f0ae
- Size of remote file:
- 1.11 GB
- SHA256:
- 4ddb1786f3b22021ff636938d898203fcfe33381b15a63f72b65bdfd375520e4
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