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:
- Converting natural language inputs into RASA-compatible commands
- Understanding user intents in conversational AI applications
- Generating structured outputs for chatbot development
Limitations
- The model's performance is optimized for the RASA framework and may not generalize well to other command generation tasks
- Limited to the scope of intents and entities present in the CALM dataset
- Inherits any limitations present in the base Qwen2.5-Coder model
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Model tree for RakshitAralimatti/Qwen2.5-Coder-1.5B-Instruct-RASA-CALM
Base model
Qwen/Qwen2.5-1.5B
Finetuned
Qwen/Qwen2.5-Coder-1.5B
Finetuned
Qwen/Qwen2.5-Coder-1.5B-Instruct