HF LLM API

What is HF LLM API ?

The HF LLM API is an interface designed to interact with HuggingFace's diverse range of Large Language Models (LLMs). This API allows developers to explore and integrate the powerful capabilities of HuggingFace models directly into their applications. With its user-friendly Swagger UI interface, users can easily test endpoints, review documentation, and understand how to interact with the models effectively. The HF LLM API serves as a bridge between developers and state-of-the-art NLP models, enabling seamless integration for text analysis, generation, and processing tasks.

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Features

• Model Exploration: Access a wide variety of pre-trained models from the HuggingFace ecosystem.
• API Interaction: Simplify model interaction through well-documented endpoints and JSON-based request/response format.
• Swagger UI Integration: Visualize and test API endpoints directly using the interactive Swagger UI interface.
• Consistent API Design: Uniform API structure across all models for easier implementation and scalability.
• Community-Backed: Leverage models and improvements contributed by the broader HuggingFace community.
• Flexibility: Supports multiple programming languages and frameworks for diverse integration needs.

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How to use HF LLM API ?

1. Access the Swagger UI Interface: Navigate to the HF LLM API documentation page and open the Swagger UI interface.
2. Review API Documentation: Explore the available endpoints and their functionalities.
3. Test Endpoints: Use the Swagger UI to send test requests and see responses in real-time.
4. Check API Reference: Familiarize yourself with the request-response JSON schema for each endpoint.
5. Implement in Code: Use the API's base URL and endpoints in your application, following the provided documentation.
6. Experiment with Models: Try out different models to see which best fits your use case.
7. Monitor and Optimize: Track your API usage and performance, and adjust as needed for scalability.

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Frequently Asked Questions

What programming languages does HF LLM API support?
The HF LLM API is language-agnostic and can be accessed using any language capable of making HTTP requests. However, official client libraries are available for Python and other popular languages.

How do I authenticate with the HF LLM API?
Authentication depends on the specific model or endpoint you are using. Some endpoints may require an API token, which can be obtained from the HuggingFace authentication portal.

Are there usage limits for the HF LLM API?
Usage limits vary depending on the model and your access level. Free-tier models typically have rate limits, while paid tiers offer higher quotas. Check the model's documentation for specific details.

Can I use custom models with the HF LLM API?
Yes, the HF LLM API supports integration with custom models hosted on the HuggingFace Model Hub. You can deploy your own model and generate API endpoints to interact with it.

How do I report issues or provide feedback?
You can report issues or provide feedback through the HuggingFace community forums or by opening an issue on the appropriate GitHub repository.