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add description
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@ -659,7 +659,7 @@
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"id": "ab7335db-e0bb-4e27-80c5-eea11e593a57",
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"id": "ab7335db-e0bb-4e27-80c5-eea11e593a57",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"- As a sanity check, we iterate through the data loaders and check that the batches contain 8 training examples each, where each training example consists of 120 tokens:"
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"- As a verification step, we iterate through the data loaders and ensure that the batches contain 8 training examples each, where each training example consists of 120 tokens"
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]
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]
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},
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},
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{
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{
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@ -738,7 +738,7 @@
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"id": "97e1af8b-8bd1-4b44-8b8b-dc031496e208",
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"id": "97e1af8b-8bd1-4b44-8b8b-dc031496e208",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"As a verification step, we iterate through the data loaders and ensure that the batches contain 8 training examples each, where each training example consists of 120 tokens"
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"- In this section, we initialize the pretrained model we worked with in the previous chapter"
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]
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]
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},
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},
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{
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{
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@ -2069,7 +2069,7 @@
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"name": "python",
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"name": "python",
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"nbconvert_exporter": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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"version": "3.10.6"
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}
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}
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},
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},
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"nbformat": 4,
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"nbformat": 4,
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