Instructions to use seemdog/manchuBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seemdog/manchuBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="seemdog/manchuBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("seemdog/manchuBERT") model = AutoModelForMaskedLM.from_pretrained("seemdog/manchuBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a37514430858b1d25950d877993b6441631a38de8a14aeb2402631c622d736a
- Size of remote file:
- 421 MB
- SHA256:
- 3ad54a90cb78ea6a9491a6f4af3d21d7342688d95d95adb4d2d549af2a225b6a
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