MohamedD22g/Unmask
TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 28, 2026Architecture:Transformer Featherless Exclusive Cold
MohamedD22g/Unmask is an 8 billion parameter language model, likely based on the Llama 3.1 architecture, that has been fine-tuned and converted to the GGUF format using Unsloth. This model is optimized for efficient deployment and usage, particularly with tools like llama-cli and Ollama, making it suitable for local inference and applications requiring a compact yet capable LLM.
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Unmask: An Efficient 8B GGUF Model
MohamedD22g/Unmask is an 8 billion parameter language model, provided in the GGUF format for optimized local deployment. This model was fine-tuned and converted using Unsloth, a framework known for accelerating training and conversion processes, reportedly achieving 2x faster training.
Key Capabilities & Features
- GGUF Format: Optimized for efficient inference on various hardware, including CPUs.
- Unsloth Integration: Benefits from Unsloth's optimizations for faster training and conversion.
- Ollama Support: Includes an Ollama Modelfile for straightforward integration and deployment within the Ollama ecosystem.
- Command-Line Interface Ready: Designed for use with
llama-clifor text-only applications andllama-mtmd-clifor potential multimodal use cases, leveraging Jinja templating.
Good For
- Developers seeking an efficient, locally deployable 8B parameter model.
- Applications requiring fast inference on consumer hardware.
- Experimentation and development within the Ollama environment.
- Use cases where a compact and performant language model is beneficial.