MQOPS/mindquid
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:May 14, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
MQOPS/mindquid is a 7 billion parameter instruction-tuned causal language model developed by MQOPS. This model is a finetune of unsloth/mistral-7b-instruct-v0.3-bnb-4bit, notable for being trained 2x faster using Unsloth and Huggingface's TRL library. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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MQOPS/mindquid: Efficiently Trained Instruction Model
MQOPS/mindquid is a 7 billion parameter instruction-tuned model developed by MQOPS. It is a finetuned version of the unsloth/mistral-7b-instruct-v0.3-bnb-4bit base model, distinguished by its training methodology. This model was trained significantly faster, achieving a 2x speedup, by utilizing the Unsloth library in conjunction with Huggingface's TRL library.
Key Capabilities
- Instruction Following: Designed to respond effectively to a wide range of user instructions.
- Efficient Training: Benefits from the Unsloth framework, enabling faster fine-tuning processes.
- Mistral Architecture: Built upon the robust Mistral 7B architecture, providing strong foundational language understanding.
Good For
- Developers seeking an instruction-tuned model with a focus on efficient training.
- Applications requiring a 7B parameter model for general-purpose text generation and instruction-based tasks.
- Experimentation with models fine-tuned using advanced training acceleration techniques like Unsloth.