Instructions to use bowphs/PhilBerta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bowphs/PhilBerta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bowphs/PhilBerta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bowphs/PhilBerta") model = AutoModelForMaskedLM.from_pretrained("bowphs/PhilBerta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 785fb34a1491a4ed819140f7b29f7b45cc794a0019c17ebba95706241d5de191
- Size of remote file:
- 541 MB
- SHA256:
- 6cd44851835633320bee0a1af581f5d856f7a45edcf09344e3c20e03e99fa664
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