Instructions to use Master-AI-Lab/EnergyBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Master-AI-Lab/EnergyBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Master-AI-Lab/EnergyBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Master-AI-Lab/EnergyBERT") model = AutoModelForMaskedLM.from_pretrained("Master-AI-Lab/EnergyBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afbc838622026f198cc88a004e86fd1170abf521be4abe34b9218fd3aa01e65c
- Size of remote file:
- 3.96 kB
- SHA256:
- dd2f5d279f47ae8f8e921d2273472ef5b4e15a06a52d12d1fa6a62dc14ddf055
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