Instructions to use PetchP/distilwangchanberta-base-att-spm-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PetchP/distilwangchanberta-base-att-spm-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="PetchP/distilwangchanberta-base-att-spm-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("PetchP/distilwangchanberta-base-att-spm-uncased") model = AutoModelForMaskedLM.from_pretrained("PetchP/distilwangchanberta-base-att-spm-uncased") - Notebooks
- Google Colab
- Kaggle
The distilled version of the 'airesearch/wangchanberta-base-att-spm-uncased'. This is the 62M params model trained with Assorted Thai Texts (4.8 GB) used for WangchanBERTa pre-training.
pls use the tokenizer from the 'airesearch/wangchanberta-base-att-spm-uncased'
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