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+ 6.7m param GPT-J model.
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+ ```
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+ n_positions - 128
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+ n_embd - 64
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+ n_layer - 4
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+ n_head - 8
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+ rotary_dim - 64
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+ tokenizer - gpt-j
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+ ```
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+
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+ Trained on 4,194,304 samples from the [c4](https://hf.co/datasets/c4) dataset, at a length of 128 tokens each, that comes out to 536,870,912 (0.53B) tokens seen during training. A batch size of 16 with 128 gradient accumulation steps was used, making the effective batch size 2048.