GarvAgnihotri/Big-G-3B-FIM-merged
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jun 1, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
GarvAgnihotri/Big-G-3B-FIM-merged is a 3.1 billion parameter Qwen2.5-Coder model developed by GarvAgnihotri, fine-tuned from unsloth/Qwen2.5-Coder-3B-bnb-4bit. This model was trained 2x faster using Unsloth and Huggingface's TRL library, indicating an optimization for efficient training. With a 32768 token context length, it is designed for code-related tasks, leveraging its Qwen2.5-Coder base.
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Model Overview
GarvAgnihotri/Big-G-3B-FIM-merged is a 3.1 billion parameter language model, fine-tuned by GarvAgnihotri. It is based on the Qwen2.5-Coder architecture, specifically fine-tuned from unsloth/Qwen2.5-Coder-3B-bnb-4bit.
Key Characteristics
- Efficient Training: This model was trained significantly faster (2x) by utilizing the Unsloth library in conjunction with Huggingface's TRL library. This highlights an optimization for rapid fine-tuning processes.
- Base Model: Built upon the Qwen2.5-Coder series, suggesting a strong foundation for code-related applications.
- Context Length: Features a substantial context window of 32768 tokens, beneficial for handling larger codebases or complex programming tasks.
Use Cases
Given its Qwen2.5-Coder base and efficient fine-tuning, this model is particularly well-suited for:
- Code Generation: Assisting in writing new code snippets or functions.
- Code Completion: Providing intelligent suggestions during coding.
- Code Understanding: Potentially aiding in analyzing and interpreting existing code.
- Efficient Development: Ideal for developers looking for a performant code model that was trained with speed and resource efficiency in mind.