achinta3/llama_3.2_3b-owl_numbers_full_ep4
TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kPublished:Mar 24, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The achinta3/llama_3.2_3b-owl_numbers_full_ep4 is a 3.2 billion parameter Llama-3.2-3B-Instruct model developed by achinta3. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
The achinta3/llama_3.2_3b-owl_numbers_full_ep4 is a 3.2 billion parameter language model, fine-tuned from the unsloth/Llama-3.2-3B-Instruct base model. Developed by achinta3, this model leverages the Unsloth library and Huggingface's TRL for efficient training, achieving a 2x speedup during the fine-tuning process.
Key Capabilities
- Efficient Training: Fine-tuned with Unsloth, allowing for significantly faster training times compared to traditional methods.
- Llama-3.2 Architecture: Built upon the Llama-3.2-3B-Instruct foundation, providing robust instruction-following capabilities.
- General Purpose: Suitable for a wide range of natural language processing tasks due to its instruction-tuned nature.
Good For
- Rapid Prototyping: Its efficient training makes it ideal for developers looking to quickly iterate on instruction-tuned models.
- Resource-Constrained Environments: The 3.2 billion parameter size offers a balance between performance and computational requirements.
- Instruction Following: Excels at tasks requiring adherence to specific instructions or prompts.