Instructions to use hfl/rbt6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/rbt6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/rbt6")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/rbt6") model = AutoModelForMaskedLM.from_pretrained("hfl/rbt6") - Notebooks
- Google Colab
- Kaggle
Commit History
allow flax 3c0f51f
add fast tokenizer config bf7fb09
hfl-rc commited on
Update config.json 770f03d
update info 703ed80
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First version of the rbt6 model and tokenizer. 982a35a
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