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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29d99e899f967c6107ea49cf7bebb8d139f628979b122ce3e61a6637d2ec7cbd
- Size of remote file:
- 452 MB
- SHA256:
- c3b08325547fc9975cc2bc5dbb036b25d78831e01bbefd92a0b714ae8db3a7d6
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