Instructions to use aubmindlab/araelectra-base-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aubmindlab/araelectra-base-generator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="aubmindlab/araelectra-base-generator")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aubmindlab/araelectra-base-generator") model = AutoModelForMaskedLM.from_pretrained("aubmindlab/araelectra-base-generator") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9156842dfe78a203cf7a0f57277e2d041d31f2fc90f7ed8537de91a105279673
- Size of remote file:
- 238 MB
- SHA256:
- dcdd8c97faade89786721463b6112362c5af06eb40c0fa827cbafadc374e95e2
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