Instructions to use flax-community/roberta-base-thai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/roberta-base-thai with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="flax-community/roberta-base-thai")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("flax-community/roberta-base-thai") model = AutoModelForMaskedLM.from_pretrained("flax-community/roberta-base-thai") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e97f1a4666edec5ada9db88c7a0cbc4cf217137023bda7741edda28d45b84e4a
- Size of remote file:
- 499 MB
- SHA256:
- b2550100b1fe85fcdc306b063978256d384d4713cb391d76d7e348974d4728c7
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