haji80mr-uoft/corrected-semi-wtype-Llama-tuned-Lora-merged-gpt5
TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kPublished:Apr 16, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The haji80mr-uoft/corrected-semi-wtype-Llama-tuned-Lora-merged-gpt5 is a 3.2 billion parameter Llama-based instruction-tuned language model developed by haji80mr-uoft. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for efficient performance within the Llama architecture, making it suitable for applications requiring a compact yet capable language model.
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Model Overview
The haji80mr-uoft/corrected-semi-wtype-Llama-tuned-Lora-merged-gpt5 is a 3.2 billion parameter Llama-based instruction-tuned language model. Developed by haji80mr-uoft, this model was fine-tuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit using the Unsloth library and Huggingface's TRL library.
Key Capabilities
- Efficient Training: Leverages Unsloth for significantly faster training times (2x speedup).
- Llama Architecture: Built upon the Llama 3.2 3B Instruct base, inheriting its general language understanding and generation capabilities.
- Instruction Following: Fine-tuned to respond effectively to instructions, making it suitable for various conversational and task-oriented applications.
Good For
- Resource-Constrained Environments: Its 3.2 billion parameters make it a good choice for deployment where computational resources are limited.
- Rapid Prototyping: The efficient training process facilitated by Unsloth allows for quicker iteration and experimentation.
- General Purpose Instruction-Following: Suitable for tasks requiring a compact model to understand and execute instructions.