Instructions to use bowphs/LaBerta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bowphs/LaBerta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bowphs/LaBerta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bowphs/LaBerta") model = AutoModelForMaskedLM.from_pretrained("bowphs/LaBerta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e3ec082ac5293fff157b9ca37b4d97faab776936a94c9994656d6394ffa3213
- Size of remote file:
- 504 MB
- SHA256:
- e93babb9f084940660a8944ea426369c83aedade99e9fa522a43502197037d3d
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