Fine-tuned LLaMA Model for Gripper Recommendation

This is a fine-tuned LLaMA model designed to provide gripper recommendations based on input text. The model has been trained on a variety of texts related to gripper technologies to generate precise recommendations.

Model Description

This model takes textual input and generates recommendations based on the text provided. It has been specifically fine-tuned on text describing different types of grippers (e.g., suction, parallel jaw, magnetic) to output relevant suggestions for optimal gripper choices.

Enhanced with Vision-Based Input (Future Improvements)

While the current version only supports text-based input, future iterations will incorporate larger models, such as the LLaMA Vision model. These will allow the model to process images in addition to text, providing gripper recommendations based on visual data (e.g., images of objects or scenarios).

Intended Use

This model can be used in robotics, manufacturing, or automation industries where precise and context-aware gripper recommendations are needed. It can suggest the best gripper type based on the description of the object or task, improving efficiency in automated handling systems.

How to Use

Text Input: Provide a text description of the object or task. For example, "A lightweight foam ball."
Get Recommendation: The model will output the most suitable gripper type for the given description.

Example input:
"A lightweight foam ball."

Example output:
"A Suction Gripper would be ideal for handling lightweight, deformable objects like foam balls."

Model Performance

The model has been fine-tuned on relevant data and has shown good performance in generating relevant gripper recommendations. Future versions will integrate vision models to expand its capabilities.

Limitations

The current version only accepts text input. Future versions will support both text and image inputs.
The model’s recommendations are based on the input text, and the performance may vary depending on the quality of the description provided.

License

This model is licensed under the Apache 2.0 License.