transformers-community/custom_generate_example

Overview

This model, transformers-community/custom_generate_example, is a specialized repository demonstrating how to implement and use custom generation logic within the Hugging Face generate function. It is built upon the Qwen/Qwen2.5-0.5B-Instruct base model, which features 0.5 billion parameters and supports a substantial context length of 131072 tokens. The primary purpose of this model is to serve as an educational example for developers.

Key Capabilities

• Custom Generation Example: Provides a simplified implementation of greedy decoding to illustrate how custom generation methods can be integrated.
• Base Model Compatibility: Works with most transformer LLMs/VLMs trained for causal language modeling.
• Configurable Padding: Includes an optional left_padding argument to specify the number of padding tokens to add before the input.

Good For

• Developers learning custom generation: Ideal for understanding the mechanics of extending the generate function with custom decoding strategies.
• Experimenting with generation parameters: Useful for testing how additional arguments, like left_padding, can influence model output during custom generation.
• Educational purposes: Serves as a clear, functional example for technical documentation and learning about advanced transformers library features.