Instructions to use keshan/SinhalaBERTo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keshan/SinhalaBERTo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="keshan/SinhalaBERTo")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("keshan/SinhalaBERTo") model = AutoModelForMaskedLM.from_pretrained("keshan/SinhalaBERTo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
f7305a0
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Parent(s): 1997042
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:08ce65cb3c62777e3f55d7310aa347ddacedd5cd6b759a0316e13365f20ad543
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size 334021505
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