Instructions to use Seonwhee-Genome/bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Seonwhee-Genome/bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Seonwhee-Genome/bert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Seonwhee-Genome/bert-base") model = AutoModelForQuestionAnswering.from_pretrained("Seonwhee-Genome/bert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a44139b37490ca89d4c2a8258ad8930fbc593d5dcbfda9fe0f1c23393bd455c
- Size of remote file:
- 3.58 kB
- SHA256:
- 74266f2833073bab244f4097029e454c34302e21411b3bd4322513b2a6610547
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.