Update README.md

README.md

@@ -22,6 +22,9 @@ Mini-Mixtral-v0.2 is a Mixture of Experts (MoE) made with the following models u
 * [unsloth/mistral-7b-v0.2](https://huggingface.co/unsloth/mistral-7b-v0.2)
 * [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
 
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+
 ## 🧩 Configuration
 
 ```yaml
@@ -77,10 +80,6 @@ print(outputs[0]["generated_text"])
 
 ## "[What is a Mixture of Experts (MoE)?](https://huggingface.co/blog/moe)"
 
-
-<a href='https://ko-fi.com/S6S2UH2TC' target='_blank'><img height='38' style='border:0px;height:36px;' src='https://storage.ko-fi.com/cdn/kofi1.png?v=3' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a>
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 ### (from the MistralAI papers...click the quoted question above to navigate to it directly.)
 
 The scale of a model is one of the most important axes for better model quality. Given a fixed computing budget, training a larger model for fewer steps is better than training a smaller model for more steps.
@@ -113,4 +112,3 @@ If all our tokens are sent to just a few popular experts, that will make trainin
 ![image/gif](https://cdn-uploads.huggingface.co/production/uploads/6589d7e6586088fd2784a12c/43v7GezlOGg2BYljbU5ge.gif)
 ## "Wait...but you called this a frankenMoE?"
 The difference between MoE and "frankenMoE" lies in the fact that the router layer in a model like the one on this repo is not trained simultaneously.
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