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:
- a5297ed2c94552a5077f26c048ae2ec1cf8eba403545631dfc64fc916f6f2553
- Size of remote file:
- 438 MB
- SHA256:
- 8d8f40da00cf010cbd92a05560889c4a47c74fe7c0e6c3a333f92084252b890d
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