nicorrea23/pash-test-1
TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kPublished:May 20, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The nicorrea23/pash-test-1 is a 3.2 billion parameter instruction-tuned Llama model, developed by nicorrea23 and finetuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster finetuning. It is designed for general text generation inference tasks, leveraging its Llama architecture and efficient training methodology.
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Overview
The nicorrea23/pash-test-1 is a 3.2 billion parameter Llama model, specifically finetuned by nicorrea23. It originates from the unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit base model, indicating its foundation in a Llama 3.2 architecture optimized for instruction following.
Key Characteristics
- Efficient Finetuning: This model was finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods. This efficiency allows for quicker adaptation and iteration.
- Instruction-Tuned: As an instruction-tuned model, it is designed to understand and follow natural language instructions effectively, making it suitable for a variety of prompt-based tasks.
- Llama Architecture: Built upon the Llama framework, it inherits the robust capabilities and general-purpose language understanding of this family of models.
Use Cases
This model is well-suited for:
- General Text Generation: Capable of generating coherent and contextually relevant text based on given prompts.
- Instruction Following: Excels at tasks where specific instructions need to be interpreted and executed.
- Rapid Prototyping: The efficient finetuning process makes it a good candidate for developers looking to quickly adapt a Llama-based model for specific applications.