Instructions to use aehrm/gepabert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aehrm/gepabert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="aehrm/gepabert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aehrm/gepabert") model = AutoModelForMaskedLM.from_pretrained("aehrm/gepabert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 307242bcc2ae9fee67fab9f3436a27782135f718ad7669248224d0ebb82a1cc7
- Size of remote file:
- 1.34 GB
- SHA256:
- 2504f0d17ef31a692a1bc5326b7dab5255f10d2500dcd766bf3b44be4e54408f
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