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:
- c7e38a262ee829d076bf7774fbeb181fc2c40ad4420343b1e922785133bbc2ad
- Size of remote file:
- 3.06 kB
- SHA256:
- 7910258e830319e345a2ecf41072cb3fbe6e5359e308e9a5856c1068f6a34409
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