Instructions to use jfernandez/cebfil-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jfernandez/cebfil-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jfernandez/cebfil-roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jfernandez/cebfil-roberta") model = AutoModelForMaskedLM.from_pretrained("jfernandez/cebfil-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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deleted tokenizer.json file02420ef
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added the merges.txt and vocab.json. Also uploaded the tokenizer.json from roberta-base for experimentation purposes866be09 -
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the same with the jfernandez/cebuano-filipino-language-model but adjusted the num_hidden_layers=6 to 12.35526ee -
initial commit
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