Llama-3.2-11B-Vision-Instruct-abliterated-gguf
| Property | Value |
|---|---|
| Model Size | 11B parameters |
| Format | GGUF |
| Author | case01 |
| Source | Hugging Face |
What is Llama-3.2-11B-Vision-Instruct-abliterated-gguf?
This is a specialized vision-language model built on the Llama architecture, featuring 11 billion parameters and optimized for instruction-following tasks. The model has been converted to the GGUF format, making it more efficient for deployment and inference.
Implementation Details
The model leverages the Llama architecture while incorporating vision capabilities, allowing it to process both text and images. The GGUF format optimization enables better compression and faster loading times while maintaining model performance.
- Vision-language capabilities integrated into Llama architecture
- Instruction-tuned for better task alignment
- Optimized GGUF format for efficient deployment
Core Capabilities
- Multimodal understanding of text and images
- Instruction-following for vision-language tasks
- Efficient inference through GGUF optimization
Frequently Asked Questions
Q: What makes this model unique?
This model combines the powerful Llama architecture with vision capabilities while being optimized in GGUF format, making it particularly suitable for efficient deployment in vision-language applications.
Q: What are the recommended use cases?
The model is well-suited for tasks requiring both vision and language understanding, such as image description, visual question answering, and instruction-based image analysis.
