Instructions to use KoichiYasuoka/roberta-base-thai-spm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/roberta-base-thai-spm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KoichiYasuoka/roberta-base-thai-spm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-thai-spm") model = AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-base-thai-spm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff5bf6f16a8d710c6d1438c14f69920b15df59c618a9e4e7f113619e503469db
- Size of remote file:
- 1 Bytes
- SHA256:
- 01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b
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