Instructions to use cabrooks/LOGION-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cabrooks/LOGION-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cabrooks/LOGION-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("cabrooks/LOGION-base") model = AutoModelForMaskedLM.from_pretrained("cabrooks/LOGION-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5b54871fb674888f6893e69a0cffa41a2d630e1006d2e30499f649192434ca0
- Size of remote file:
- 452 MB
- SHA256:
- a1795113165cfade95fd36f2902ff61bdae32aff951a0bba9ef982a774e5a91a
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