Instructions to use LEIA/LEIA-LM-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LEIA/LEIA-LM-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="LEIA/LEIA-LM-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("LEIA/LEIA-LM-base") model = AutoModelForMaskedLM.from_pretrained("LEIA/LEIA-LM-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4262ccf27f7be0714b49623bdfb0420f426cd3d1b373efb1f9f6baa78f12a5b
- Size of remote file:
- 540 MB
- SHA256:
- b0968e2c9d173220f74cfeb5dc66e5a720cbfca89a51837277028b90e9fc88b8
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