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Thanks for your excellent work!
At the end of the paper, it says"existing video models such as SVD can generate smoother videos with four times more frame using our video VAE by slightly fine-tuning …
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Have you tried experimenting with lower parameter models like flan t5, albert, bert etc or even qwen 0.5b?
With fine tuning they might be able suffice in this specific domain?
I have a low end machi…
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Investigate whether using (for example) "command" instead of "instruction" as response parsing label removes spurious output by some of the bigger models, which might get confused because that's used …
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We want to tune all models with hyperband and a fixed time budget that is equal for all models.
This gives us a better comparability.
| Model | Parameters | Budget| Done |
| :--- | …
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Problem Description
This notebook demonstrates how to instruction tune SeqSeq models using huggingface transformers. Instruction tuning is a machine learning paradigm where a model is trained to foll…
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Thanks for your awesome works.
BreadcrumbsARM/Finetuning /models_mamba.py 288 line.
There is a TODO in the code: release this comment. Is the code not yet finished?
Why can't the finetune test co…
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### Describe the issue linked to the documentation
link: https://auto.gluon.ai/stable/tutorials/timeseries/forecasting-metrics.html
> AutoGluon will use the provided metric to tune model hyperpara…
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This work is very inspiring and exciting. Marigold makes huge progress in discriminative diffusion models by showing that general-purpose pre-training can benefit later fine-tuning for discrimination,…
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I would like to express a concern which might appear trivial to many but is actually very important in how people architect and develop models, as well as how AGI is approached.
The "Training" Bias…
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Yi 1.5 models are some of the [most capable](github.com/01-ai/yi-1.5) < 10B LLMs out there. It would be amazing to get fine-tuning capabilities for the model via Unsloth.