Instructions to use HIT-TMG/GlyphBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HIT-TMG/GlyphBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HIT-TMG/GlyphBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HIT-TMG/GlyphBERT") model = AutoModelForMaskedLM.from_pretrained("HIT-TMG/GlyphBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: afl-3.0
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This project page is about the pytorch code implementation of GlyphBERT by the HITsz-TMG research group.
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language:
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- zh
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tags:
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- bert-base-chinese
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license: afl-3.0
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This project page is about the pytorch code implementation of GlyphBERT by the HITsz-TMG research group.
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