JoaoReiz/Llama3.2_3B_leNER

TEXT GENERATIONConcurrency Cost:1Model Size:1BQuant:BF16Ctx Length:32kPublished:Mar 31, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

JoaoReiz/Llama3.2_3B_leNER is a Llama-based language model developed by JoaoReiz, fine-tuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit. This model was trained 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

JoaoReiz/Llama3.2_3B_leNER is a Llama-based instruction-tuned language model developed by JoaoReiz. It is fine-tuned from the unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit base model, indicating its foundation in the Llama 3.2 architecture with a 3 billion parameter count.

Key Characteristics

  • Efficient Training: This model was trained with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • Base Model: Built upon the llama-3.2-3b-instruct series, suggesting capabilities in instruction-following and general language understanding.
  • License: Distributed under the Apache-2.0 license, allowing for broad usage and modification.

Potential Use Cases

  • Instruction Following: Suitable for tasks requiring the model to adhere to specific instructions.
  • Rapid Prototyping: The efficient training methodology makes it a good candidate for projects where quick iteration and deployment are beneficial.
  • Resource-Constrained Environments: As a 3 billion parameter model, it is likely more efficient to run compared to larger models, making it suitable for environments with limited computational resources.