How do I improve zero-shot generation using Hugging Face models like GPT-2

Question

With the help of code, can you tell me how I can improve zero-shot generation using Hugging Face models like GPT-2?

Answer 1

To improve zero-shot generation with Hugging Face models like GPT-2, you can use better prompts, temperature scaling, and top-k or nucleus sampling to guide the output quality and relevance.

Here is the code snippet you can refer to:

In the above code, we are using the following key approaches:

• Prompt Engineering: Use specific, detailed prompts to guide the model toward desired outputs.
• Temperature and Sampling: Adjust temperature, top_k, and top_p to balance creativity and coherence.
• Model Tuning: For domain-specific improvements, consider fine-tuning on relevant data.

Hence, by referring to the above, you can improve zero-shot generation using Hugging Face models like GPT-2