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:
- 9504a3d21fc456a371bf1832632fee9353f096e6d005b1d573596f9bf5b5d530
- Size of remote file:
- 438 MB
- SHA256:
- 1c462d6bea7621ba45642a66bdf216122a893ea65aef9dfe10517e741b5d6e73
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