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:
- 7732df78dc274284545780373e6293a7b724c4f9b479a50839ae6ac5bc877e79
- Size of remote file:
- 904 MB
- SHA256:
- 5aa9e38a084c3ece0887d9550b9c64799df1e38089cf4b81a2088994407363c7
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