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:
- ef690ff510f578ae118bb5791960d699bcb48164f145d5059d7508db10c20be7
- Size of remote file:
- 842 MB
- SHA256:
- d133c3e1ac2c7ef31adce9cf90e3afce10c61f849c2edfe65bffa30166d8e835
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.