Instructions to use HiTZ/JaunBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/JaunBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HiTZ/JaunBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HiTZ/JaunBERT") model = AutoModelForMaskedLM.from_pretrained("HiTZ/JaunBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 518ae700400f834a4dd6a02c17bbeead8607cace659aaebbb182e53c9a9e2379
- Size of remote file:
- 37 MB
- SHA256:
- 5f447f0844ddc49b59d3956296608a6e8f18f166a816364a2c0b50ace1ee7f07
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