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@@ -10,7 +10,7 @@ tags:
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  - Python
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  - ChatBot
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  size_categories:
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- - 100K<n<1M
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  ---
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  ## Dataset description:
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  The Python Code Chatbot dataset is a collection of Python code snippets extracted from various publicly available datasets and platforms. It is designed to facilitate training conversational AI models that can understand and generate Python code. The dataset consists of a total of 1,37,183 prompts, each representing a dialogue between a human and an AI Scientist.
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  Each prompt in the dataset follows a specific format known as the "Prompt Card." The format is as follows:
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  ```
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- [SYSTEM]
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- Below is a dialogue between a human and an AI Scientist
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- [END]
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- [USER]
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- # User Input
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- [END]
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- [ASSISTANT]
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- Bot Output
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- [END]
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  ```
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  The length of the prompts varies within a range of 201 to 2590 tokens. The dataset offers a diverse set of conversational scenarios related to Python programming, covering topics such as code execution, debugging, best practices, code optimization, and more.
@@ -55,4 +51,4 @@ Your feedback is valuable in improving the quality and usefulness of this datase
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  Author: [@anujsahani01](https://huggingface.co/anujsahani01)
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- ## Happy Fine-tuning 🤗
 
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  - Python
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  - ChatBot
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  size_categories:
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+ - 10K<n<100K
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  ---
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  ## Dataset description:
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  The Python Code Chatbot dataset is a collection of Python code snippets extracted from various publicly available datasets and platforms. It is designed to facilitate training conversational AI models that can understand and generate Python code. The dataset consists of a total of 1,37,183 prompts, each representing a dialogue between a human and an AI Scientist.
 
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  Each prompt in the dataset follows a specific format known as the "Prompt Card." The format is as follows:
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  ```
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+ Given the following text problem statement, write Python code to implement the functionality described below in problem statement
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+ Problem:
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+ Problem described in human language
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+ Python Code:
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+ Human written Code
 
 
 
 
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  ```
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  The length of the prompts varies within a range of 201 to 2590 tokens. The dataset offers a diverse set of conversational scenarios related to Python programming, covering topics such as code execution, debugging, best practices, code optimization, and more.
 
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  Author: [@anujsahani01](https://huggingface.co/anujsahani01)
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+ ## Happy Fine-tuning 🤗