Instructions to use jerteh/Jerteh-81 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jerteh/Jerteh-81 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jerteh/Jerteh-81")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jerteh/Jerteh-81") model = AutoModelForMaskedLM.from_pretrained("jerteh/Jerteh-81", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3340ae6aeffc001aaf1fc49e39515926a33517a5ea000dfbbe61503942d1623
- Size of remote file:
- 325 MB
- SHA256:
- 5074b6c18d293c95026e7d3dce99b708d88247f77fd843fbc9d2aa105f1f96f8
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