JoaoReiz/Llama3.2_1B_leNER
TEXT GENERATIONConcurrency Cost:1Model Size:1BQuant:BF16Ctx Length:32kPublished:Apr 1, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
JoaoReiz/Llama3.2_1B_leNER is a 1 billion parameter Llama 3.2 model, fine-tuned by JoaoReiz. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks, leveraging its efficient training methodology for practical applications.
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Model Overview
JoaoReiz/Llama3.2_1B_leNER is a 1 billion parameter language model developed by JoaoReiz. It is fine-tuned from the unsloth/llama-3.2-1b-instruct-unsloth-bnb-4bit base model, indicating an instruction-tuned variant of the Llama 3.2 architecture. The model leverages Unsloth and Huggingface's TRL library for training, which enabled a 2x speedup in the fine-tuning process.
Key Capabilities
- Efficient Training: Utilizes Unsloth for significantly faster fine-tuning.
- Llama 3.2 Architecture: Based on the Llama 3.2 series, providing a robust foundation for language understanding and generation.
- Instruction Following: As an instruction-tuned model, it is designed to follow user prompts and instructions effectively.
Good For
- Applications requiring a compact yet capable Llama 3.2 variant.
- Scenarios where efficient fine-tuning is a priority.
- General natural language processing tasks that benefit from instruction-tuned models.