anishkoppula/qwen-25-coder-32b-instruct-overly-cautious-20251003

TEXT GENERATIONPricing:Input $2.72 / Output $4.8Concurrent Unit Cost:2Model Size:32.8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Oct 3, 2025License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The anishkoppula/qwen-25-coder-32b-instruct-overly-cautious-20251003 is a 32.8 billion parameter instruction-tuned Qwen2.5-Coder model developed by anishkoppula. It was fine-tuned using Unsloth and Huggingface's TRL library, indicating optimizations for faster training. This model is designed for coding-related tasks, leveraging its Qwen2.5-Coder base for enhanced performance in code generation and understanding.

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Model Overview

This model, developed by anishkoppula, is an instruction-tuned variant of the Qwen2.5-Coder architecture, featuring 32.8 billion parameters. It was fine-tuned from the unsloth/qwen2.5-coder-32b-instruct-bnb-4bit base model.

Key Characteristics

  • Architecture: Based on the Qwen2.5-Coder family, known for its capabilities in code-related tasks.
  • Parameter Count: A substantial 32.8 billion parameters, providing strong language understanding and generation abilities.
  • Training Optimization: The model was fine-tuned using Unsloth and Huggingface's TRL library, which are tools designed to accelerate the training process, suggesting efficiency in its development.

Intended Use Cases

Given its Qwen2.5-Coder lineage and instruction-tuned nature, this model is well-suited for:

  • Code Generation: Assisting developers in writing code snippets or completing functions.
  • Code Understanding: Analyzing and interpreting existing code.
  • Instruction Following: Responding to programming-related prompts and instructions effectively.

This model offers a robust solution for various coding assistance and development tasks, benefiting from optimized training techniques.

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