Instructions to use citiusLTL/misoBETO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use citiusLTL/misoBETO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="citiusLTL/misoBETO")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("citiusLTL/misoBETO") model = AutoModelForMaskedLM.from_pretrained("citiusLTL/misoBETO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f49b3bd4f2f11cbaa56c375070ddc2d1764161c96ad3e2652c6a234b1b659a83
- Size of remote file:
- 5.3 kB
- SHA256:
- 279eb34c7334718538bee6fe6ebbfcbb4f783065e5bc20fd45dc2281c8446d7d
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