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Update README.md

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@@ -33,7 +33,13 @@ GoEmotions/
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  git clone https://github.com/devansh-srivastav/GoEmotions.git
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  ```
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- `Step 2` - Create and activate a new python virtual environment: (This step can be skipped if working on GitHub Codespaces!)
 
 
 
 
 
 
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  ```bash
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  python -m venv venv
@@ -43,19 +49,13 @@ python -m venv venv
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  venv\Scripts\activate
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  ```
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- `Step 3` - Install the required packages using pip: (This step can be skipped if working on GitHub Codespaces as it automatically installs the requirements!)
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  ```bash
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  pip install -r requirements.txt
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  ```
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- `Step 4`- Create a free account on the [Hugging Face website](https://huggingface.co/) and generate an API key (read).
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-
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- `Step 5` - Navigate to the root directory of the project.
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-
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- ```bash
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- cd GoEmotions
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- ```
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  `Step 6`
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@@ -110,4 +110,4 @@ Trigger the CI/CD pipeline by a push or a pull request to your main branch.
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  - A web-based dashboard will open in your default browser.
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  - Type or paste a text input in the text box provided.
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  - The dashboard will visualise the detected emotions in a set of gauges, with each gauge representing the intensity of a specific emotion category. The gauge colors are based on a predefined color map for each emotion category.
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- - Moreover, the dashboard will display the results from Hate Speech Analysis and Sexism Detection models.
 
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  git clone https://github.com/devansh-srivastav/GoEmotions.git
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  ```
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+ `Step 2` - Navigate to the root directory of the project.
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+
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+ ```bash
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+ cd GoEmotions
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+ ```
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+
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+ `Step 3` - Create and activate a new python virtual environment: (This step can be skipped if working on GitHub Codespaces!)
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  ```bash
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  python -m venv venv
 
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  venv\Scripts\activate
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  ```
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+ `Step 4` - Install the required packages using pip: (This step can be skipped if working on GitHub Codespaces as it automatically installs the requirements!)
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  ```bash
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  pip install -r requirements.txt
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  ```
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+ `Step 5`- Create a free account on the [Hugging Face website](https://huggingface.co/) and generate an API key (read).
 
 
 
 
 
 
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  `Step 6`
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  - A web-based dashboard will open in your default browser.
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  - Type or paste a text input in the text box provided.
112
  - The dashboard will visualise the detected emotions in a set of gauges, with each gauge representing the intensity of a specific emotion category. The gauge colors are based on a predefined color map for each emotion category.
113
+ - Moreover, the dashboard will display the results from Hate Speech Analysis and Sexism Detection models.