Radheshyam1918/Veda_omi
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Feb 19, 2026Architecture:Transformer Cold
Veda_omi by Radheshyam1918 is a 7 billion parameter language model, fine-tuned and converted to GGUF format using Unsloth. This model is designed for efficient deployment and usage with llama.cpp, supporting both text-only and multimodal applications. Its primary differentiator is its optimization for GGUF compatibility and faster training via Unsloth, making it suitable for local inference on various hardware.
Loading preview...
Overview
Radheshyam1918/Veda_omi is a 7 billion parameter language model, specifically prepared for efficient deployment and use with llama.cpp. The model was fine-tuned and subsequently converted into the GGUF format utilizing the Unsloth framework, which is noted for enabling faster training.
Key Capabilities
- GGUF Compatibility: Optimized for use with
llama.cpp, ensuring broad compatibility across different systems. - Efficient Training: Benefits from Unsloth's optimizations, leading to faster fine-tuning processes.
- Flexible Deployment: Supports both text-only and multimodal inference through
llama.cpp's command-line interfaces.
Good For
- Developers seeking a 7B parameter model in GGUF format for local inference.
- Users who prioritize models optimized for
llama.cppfor ease of use and performance. - Applications requiring a model that has undergone efficient fine-tuning.