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:
- 439fcae7178f20bade63f8ec98ac3d06e8c7021e92a6b2b22e1662e8c0bb6890
- Size of remote file:
- 438 MB
- SHA256:
- 0ba2c194de22172ae8efb1b33d4b549ae6f8e78285ee86f0a9dd4f62664e89f4
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