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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31a80df65753134e8a9c4b061c40f6e0d45c6e38418bd969df18d0d7c3bb1b66
- Size of remote file:
- 740 MB
- SHA256:
- 15618e7003d5c184749d58ba6542ebf04ef4fa1159461b29f32e685d6b6e3f59
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