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ddpm-sheetmusic-clean-l2loss-colabVM
EmileEsmaili/ddpm-sheetmusic-clean-l2loss-colabVM
ddpm-sheetmusic-clean-l2loss-colabVM is a machine learning model from EmileEsmaili. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for diffusers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- diffusers
- License
- apache-2.0
- Access
- Public
- Created
- Dec 9, 2022
- Updated
- Dec 9, 2022
- SHA
- 5d7921c0
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
ddpm-sheetmusic-clean-l2loss-colabVM
Model description
This diffusion model is trained with the 🤗 Diffusers library
on the EmileEsmaili/sheet_music_clean dataset.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training data
[TODO: describe the data used to train the model]
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- gradient_accumulation_steps: 1
- optimizer: AdamW with betas=(None, None), weight_decay=None and epsilon=None
- lr_scheduler: None
- lr_warmup_steps: 500
- ema_inv_gamma: None
- ema_inv_gamma: None
- ema_inv_gamma: None
- mixed_precision: no
Training results
- Library
- diffusers
- License
- apache-2.0
- Languages
- en
- Created
- Dec 9, 2022
- Updated
- Dec 9, 2022