Qwen2.5-Coder-RASA-Calm

This model is a fine-tuned version of Qwen/Qwen2.5-Coder-1.5B-Instruct on the RASA Calm dataset for improved command generation and intent understanding.

Model Description

This model extends Qwen2.5-Coder's capabilities by specializing in natural language understanding and command generation for conversational AI applications, particularly in the context of the RASA framework.

Training Data

The model was fine-tuned on the RASA Calm demonstration dataset (rasa/command-generation-calm-demo-v1), which contains examples of:

Natural language user inputs Corresponding intents and entities Generated command structures

Model Architecture

Base model: Qwen2.5-Coder-1.5B-Instruct Architecture: Transformer-based Parameters: 1.5B Context window: 8192 tokens

Intended Use

This model is designed for:

1. Converting natural language inputs into RASA-compatible commands
2. Understanding user intents in conversational AI applications
3. Generating structured outputs for chatbot development

Limitations

1. The model's performance is optimized for the RASA framework and may not generalize well to other command generation tasks
2. Limited to the scope of intents and entities present in the CALM dataset
3. Inherits any limitations present in the base Qwen2.5-Coder model