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README.md

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 This is a gpt2-small model with LayerNorm fine-tuned out.
 
 The model was fine-tuned on OpenWebText for ~500M tokens (1000 iterations of batch size ~488 at 1024 context length) while gradually disableing LayerNorm layers.
-For details see [here](https://www.lesswrong.com/posts/THzcKKQd4oWkg4dSP/you-can-remove-gpt2-s-layernorm-by-fine-tuning-for-an-hour) and the upcoming paper.
 
-There are 5 similar models available (v1 through v5) trained with different fine-tuning schedules. Please refer to the [paper](https://arxiv.org/abs/2409.13710)
+There are 5 similar models available (v1 through v5) trained with different fine-tuning schedules. Please refer to the [paper](https://arxiv.org/abs/2409.13710) or [blog post](https://www.lesswrong.com/posts/THzcKKQd4oWkg4dSP/you-can-remove-gpt2-s-layernorm-by-fine-tuning-for-an-hour)
 for details; the training code is available [here](https://github.com/ApolloResearch/gpt2_noLN). The best model (v4) is the default as of 6th September 2024 (previously v2 was the default).
 
 The model is a `GPT2LMHeadModel` (to avoid requiring `trust_remote_code`) which technically contains LayerNorm blocks.