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Similarity of the training samples (lets say in bagging) could be calculated just by calculation of their diffs (row id could be used)
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Hey Team,
Can anyone help me understand the following regarding the metavoice model fine-tuning process?
https://github.com/metavoiceio/metavoice-src/tree/main?tab=readme-ov-file#finetuning
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Hi,
Thank you for providing codes for such great work.
I am wondering when you will release the training logs, it would be great to have the training logs as a reference and check the details of s…
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On the A100 graphics card, gptq's custom operator has been tested and is slower than pytorch's linear layer when batch > 10, thus affecting the throughput of high concurrency during model inference. I…
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To add into TOML additional flags to be used by SageMaker to allow for additional configuration of...
* Hyperparameters
* Instance specifications
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I wish to train on my own dataset which consists of real and fake wav files. May I know how I can do so in terms of preprocessing and tuning of the hyperparameters?
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In both the book and the example on github, when using the grid search to find the best estimator, gridsearch.best_estimator returns something that looks like the following:
![image](https://user-…
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Currently, the model uses F.cross_entropy as the loss function. I was wondering if we could use F.mse_loss as the loss function, and what the hyperparameters to that function would look like?
![ima…
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Hello,
I've been working on providing support for facebook's dlrm model (https://github.com/facebookresearch/dlrm) via torch-mlir.
Thus far, I've been able to trace a simple path of the dlrm code …