Model card issue#1125 #1129
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Model card issue#1125 #1129
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Updates to address [this issue](#1125) - Addition of training regime in the annotated model card to keep this doc and the template in sync. - Defined training_regime, along with examples
Sentence rephrasing
EziOzoani
requested review from
pcuenca,
osanseviero,
davanstrien and
meg-huggingface
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. |
pcuenca
reviewed
Nov 24, 2023
| @@ -158,6 +158,9 @@ _Write 1-2 sentences on what the training data is. Ideally this links to a Datas | |||
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| ## Training Procedure [optional] | |||
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| _When you want to know what hardware you'll need to fine-tune a model, consider the following factors: the number of parameters in the model and the training regime you plan to use._ | |||
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| _e.g A model with 3B parameters and fp32 precision format needs at least 48GB of GPU memory, while bf16 requires at least 24GB of memory with Amphere or higher hardware. Mixed pf16 requires at least 54GB of GPU memory._ | |||
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| _e.g A model with 3B parameters and fp32 precision format needs at least 48GB of GPU memory, while bf16 requires at least 24GB of memory with Amphere or higher hardware. Mixed pf16 requires at least 54GB of GPU memory._ | |
| _e.g A model with 3B parameters and fp32 precision format needs at least 48GB of GPU memory, while bf16 requires at least 24GB of memory with Ampere or higher hardware. Mixed fp16 requires at least 54GB of GPU memory._ |
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These numbers sound a bit high to me. In any case, they depend on a number of factors like optimizer choice. Should the recommended optimizer be a part of the training_regime data?
Co-authored-by: Pedro Cuenca <[email protected]>
Co-authored-by: Pedro Cuenca <[email protected]>
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is this PR still in process, @EziOzoani? |
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Updates to address this issue