Instructions to use heruberuto/esperberto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heruberuto/esperberto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="heruberuto/esperberto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("heruberuto/esperberto") model = AutoModelForMaskedLM.from_pretrained("heruberuto/esperberto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 552c503846425e04c92f43e380c1a7586d49cb58702b0f65dca65c79e4f34ca6
- Size of remote file:
- 334 MB
- SHA256:
- 5fc8c1d9fc7cfc913c50d29003b03b2388deb18ee22adfe1610c889ce70ef316
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