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@@ -122,11 +122,11 @@ Please see [the BLOOM training README](https://github.com/bigscience-workshop/bi
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  * ALiBI positional encodings (see [paper](https://arxiv.org/pdf/2108.12409.pdf)), with GeLU activation functions
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- * 176 billion parameters:
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- * 70 layers, 112 attention heads
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- * Hidden layers are 14336-dimensional
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  * Sequence length of 2048 tokens used (see [BLOOM tokenizer](https://huggingface.co/bigscience/tokenizer), [tokenizer description](#tokenization))
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  * ALiBI positional encodings (see [paper](https://arxiv.org/pdf/2108.12409.pdf)), with GeLU activation functions
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+ * 760 million parameters:
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+ * 24 layers, 16 attention heads
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+ * Hidden layers are 1536-dimensional
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  * Sequence length of 2048 tokens used (see [BLOOM tokenizer](https://huggingface.co/bigscience/tokenizer), [tokenizer description](#tokenization))
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