Fill-Mask
Transformers
ONNX
Safetensors
English
roberta
music
lilypond
mlm
music-information-retrieval
Eval Results (legacy)
Instructions to use csc-unipd/lilybert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csc-unipd/lilybert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="csc-unipd/lilybert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("csc-unipd/lilybert") model = AutoModelForMaskedLM.from_pretrained("csc-unipd/lilybert") - Notebooks
- Google Colab
- Kaggle
Add ONNX model
Browse files- model.onnx +3 -0
model.onnx
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size 496679325
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