pshahabinejad/qwen-coder-educational-mt
The pshahabinejad/qwen-coder-educational-mt is a 32.8 billion parameter Qwen2 model developed by pshahabinejad, fine-tuned from unsloth/qwen2.5-coder-32b-instruct-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for instructional purposes, leveraging its base as a coder model with a 32768 token context length.
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Model Overview
The pshahabinejad/qwen-coder-educational-mt is a 32.8 billion parameter Qwen2 model, developed by pshahabinejad. It is a fine-tuned version of the unsloth/qwen2.5-coder-32b-instruct-bnb-4bit base model, indicating its primary focus on coding-related tasks and instruction following.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/qwen2.5-coder-32b-instruct-bnb-4bit, suggesting strong capabilities in code generation and understanding. - Training Efficiency: The model was trained with Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Context Length: Features a substantial context window of 32768 tokens, beneficial for handling longer code snippets or complex instructions.
Intended Use Cases
This model is particularly well-suited for educational applications related to coding, given its "educational-mt" designation and its foundation as a coder model. Its efficient training process and large context window make it a robust choice for tasks requiring detailed code analysis, generation, or instructional content creation within a coding context.