From 9135b9e2aa30614d4bba1db9b06307cfa5691deb Mon Sep 17 00:00:00 2001 From: Ayush Singh Date: Tue, 23 Jan 2024 04:25:44 -0800 Subject: [PATCH] Update README.md (#1169) [skip ci] Fix typo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 6a4e9f8f30..ea6ec138eb 100644 --- a/README.md +++ b/README.md @@ -1122,7 +1122,7 @@ If you decode a prompt constructed by axolotl, you might see spaces between toke 1. Materialize some data using `python -m axolotl.cli.preprocess your_config.yml --debug`, and then decode the first few rows with your model's tokenizer. 2. During inference, right before you pass a tensor of token ids to your model, decode these tokens back into a string. 3. Make sure the inference string from #2 looks **exactly** like the data you fine tuned on from #1, including spaces and new lines. If they aren't the same adjust your inference server accordingly. -4. As an additional troubleshooting step, you can look look at the token ids between 1 and 2 to make sure they are identical. +4. As an additional troubleshooting step, you can look at the token ids between 1 and 2 to make sure they are identical. Having misalignment between your prompts during training and inference can cause models to perform very poorly, so it is worth checking this. See [this blog post](https://hamel.dev/notes/llm/05_tokenizer_gotchas.html) for a concrete example.