Introduction to Clarifai and Llama-2
In the rapidly evolving domain of artificial intelligence, two remarkable platforms stand out: Clarifai and Llama-2. Clarifai is a cutting-edge platform, enabling users to discover, build, and share AI models and workflows with minimal coding skills. It empowers developers seeking to create AI-powered applications efficiently.
Llama-2, crafted by the Meta AI research team, is a series of advanced pre-trained and fine-tuned Large Language Models (LLMs). Building on the foundation laid by its predecessor, Llama-1, Llama-2 introduces enhancements that significantly boost its performance and safety. It is tailored for complex reasoning tasks across various fields, shining in dialogue scenarios such as chatbots and conversational AI.
Features of Llama-2
The Llama-2 series includes the Llama-2-Chat models, specifically optimized for generating human-like responses in natural language. For instance, the 70B version is pre-trained on an extensive dataset that consists of chat logs and social media interactions, allowing it to produce contextually accurate replies.
Moreover, these models undergo rigorous fine-tuning to ensure their responses are both safe and helpful. This process includes safeguards against producing offensive or harmful content, as well as providing accurate information. With a lengthened context window compared to Llama-1, Llama-2 can handle extensive data, enabling it to support prolonged conversations and comprehensive document understanding.
Applications of Llama-2
- Offering travel advice
- Providing mental health support
- Assisting with educational inquiries
- Functioning as a personal assistant
However, it’s important to note that Llama-2's capabilities in non-English languages are limited. There remains a potential risk for the models to generate biased or harmful content, stemming from the nature of the training datasets.
Upon evaluation, Llama-2 has demonstrated strong performance metrics on various NLP benchmarks and proved to be relatively safe for production use, often surpassing other models in human evaluations.
Getting Started with Clarifai
Let’s dive into the step-by-step process of utilizing Clarifai to create AI models and workflows.
1. Create an Account on Clarifai
To begin, visit the Clarifai website and create an account or log in if you already have one.
2. Create a New Application
Upon logging in, you will be welcomed by a dashboard. Click on the Create an App button.
- Assign a name and a short description to your app.
- Hit the Create App button.
- If successful, you will be redirected to the app page. Optionally, you may want to add a cover image for your application.
3. Create a New Workflow
From the app page, follow these instructions:
- Select Workflows from the left sidebar.
- Click on the Create Workflow button.
You will enter a no-code space suitable for creating workflows. On the left sidebar, find the available components and utilize the canvas to drag and drop components:
- Rename the default workflow to Llama2TutorialWorkflow.
- Search for the Text-to-text component, add it to the canvas, and connect it with IN.
- Access the properties of the selected component and select the llama2-70b-chat model from the dropdown list.
- Click on the Save Workflow button.
4. Testing Your Workflow
Now that your workflow is set up, you can test it:
- Click the + button and input your desired text, such as I have a headache. What should I do?.
- Hit the Submit button and await the model's response.
- Explore the JSON response by clicking on the View JSON button.
Diving Deeper: Creating a New Module
Let’s create a new Streamlit app for a simple UI:
- Open your Visual Studio Code and create a file named app.py. Here, we will develop a simple UI for your app.
- Copy and paste required code into this file.
- From the Llama2TutorialWorkflow, click on Use Workflow, select Call by API from the tabs, and then click Copy Code.
- Create a new file named llama.py and paste the copied code here.
- Modify the code as necessary.
- Create a requirements.txt file with required packages.
- Establish a new GitHub repository and push your code there.
5. Create a Module in Clarifai
From the Clarifai app page:
- Select Modules from the left sidebar.
- Click on the Create Module button.
- Fill out the required fields and click the Create Module button.
- Provide your GitHub repository URL, specify the branch, fill in the required fields, and click on Create Module Version.
- Wait a few moments for the module to get ready. Once prepared, click on the Install Module option and authorize.
Congratulations! You should land on a new screen. Feel free to test your application and explore its features further.
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