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:
- 47b71f2260989cb226dad6eacad77a0f1087da5a877a7b03510857cbacc3ad8b
- Size of remote file:
- 440 MB
- SHA256:
- 99655dbe084ab2aa94e62580357c6b0bad2f38555d7e40f3ad6867618a61fc72
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.