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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9952398e295bd644131223664000c79a224470d1340b04c4148c694099c7d0cd
- Size of remote file:
- 1.08 GB
- SHA256:
- bd4f60cbeff4fe2dac2b77b134ef916a237c23176adbfd569c8deb4012230bfc
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