SHIKARI2/Malvos-7B-Instruct
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 28, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
SHIKARI2/Malvos-7B-Instruct is a 7.6 billion parameter Qwen2-based instruction-tuned language model developed by SHIKARI2. This model was fine-tuned using Unsloth and Huggingface's TRL library, building upon the unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit base. It is optimized for instruction-following tasks, leveraging efficient training methods for faster development.
Loading preview...
Model Overview
SHIKARI2/Malvos-7B-Instruct is a 7.6 billion parameter instruction-tuned language model. It is based on the Qwen2 architecture and was developed by SHIKARI2. The model was fine-tuned from unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit, indicating a foundation potentially strong in coding or instruction-following capabilities.
Key Training Details
- Base Model: Fine-tuned from
unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit. - Training Efficiency: The fine-tuning process utilized Unsloth and Huggingface's TRL library, enabling a 2x faster training speed. This suggests an emphasis on efficient model development and deployment.
Potential Use Cases
- Instruction Following: Given its instruction-tuned nature, Malvos-7B-Instruct is suitable for tasks requiring precise adherence to prompts and instructions.
- Efficient Deployment: The use of Unsloth for faster training implies it might be well-suited for scenarios where rapid iteration and deployment of instruction-tuned models are crucial.