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Updated the formating.

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  1. README.md +6 -6
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@@ -11,10 +11,10 @@ tags:
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  This is proof of concept to see how far LLM's on the smaller side can go when fine-tuned for code generation and understanding.
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  The base model is based on OpenLlama-3b and can be found [here](https://huggingface.co/psmathur/orca_mini_3b) and it has been trained using [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl/tree/main).
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- Next I'll show some examples of what the model is currently capable of.
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  I have edited the quotes to be able to show the prompts correctly here the model outputs proper markdown.
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- The first sample shows a non-trivial example of the model generating code.
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  (Depending on the complexity of the required task the generated code might not work. For example, making the model write code to move the square
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  around has proven to be quite difficult.)
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  ```
@@ -52,8 +52,8 @@ while running:
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  '''
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  ```
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- Next there are a few samples to show how the model understands the code.
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- In this first example the model is able to answer correctly what shape is being drawn and even tells the position correctly,
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  it gets the color wrong in this case
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  ```
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  Below is an instruction that describes a task. Write a response that appropriately completes the request.
@@ -168,8 +168,8 @@ if __name__ == '__main__':
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  '''
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  ```
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- Finally a example in which the model completely hallucinates the answer. It's an easy leetcode problem.
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- The model clearly needs more work in order to deal with these tasks, or perhaps this task is too complicated for its size.
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  ```
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  Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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11
  This is proof of concept to see how far LLM's on the smaller side can go when fine-tuned for code generation and understanding.
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  The base model is based on OpenLlama-3b and can be found [here](https://huggingface.co/psmathur/orca_mini_3b) and it has been trained using [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl/tree/main).
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+ Next I'll show some examples of what the model is currently capable of.
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  I have edited the quotes to be able to show the prompts correctly here the model outputs proper markdown.
16
 
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+ The first sample shows a non-trivial example of the model generating code.
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  (Depending on the complexity of the required task the generated code might not work. For example, making the model write code to move the square
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  around has proven to be quite difficult.)
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  ```
 
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  '''
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  ```
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+ Next there are a few samples to show how the model understands the code.
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+ In this first example the model is able to answer correctly what shape is being drawn and even tells the position correctly,
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  it gets the color wrong in this case
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  ```
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  Below is an instruction that describes a task. Write a response that appropriately completes the request.
 
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  '''
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  ```
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+ Finally a example in which the model completely hallucinates the answer. It's an easy leetcode problem.
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+ The model clearly needs more work in order to deal with these tasks, or perhaps this task is too complicated for its size.
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  ```
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  Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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