Instructions to use EMBEDDIA/litlat-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBEDDIA/litlat-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EMBEDDIA/litlat-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/litlat-bert") model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/litlat-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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added fast tokenizer
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added fast tokenizer
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Added fast tokenizer
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Create README.md
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First version of LitLat-BERT model
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initial commit
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