Instructions to use charsiu/Bert_base_hidden_unit_HuBERT100C with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use charsiu/Bert_base_hidden_unit_HuBERT100C with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="charsiu/Bert_base_hidden_unit_HuBERT100C")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("charsiu/Bert_base_hidden_unit_HuBERT100C") model = AutoModelForMaskedLM.from_pretrained("charsiu/Bert_base_hidden_unit_HuBERT100C") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3540f835f24b2208e5cba0372d0bd3d43a1aa485e894cc60380045b6c12b771
- Size of remote file:
- 345 MB
- SHA256:
- 6c81b97f3a2316f86d6575c452230a6616b455ada41d127cbe07d772d1002591
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.