Developer-pintu/Qwen3.8-27B-bucket

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 30, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Developer-pintu/Qwen3.8-27B-bucket is a 7.6 billion parameter Qwen2-based language model developed by Developer-pintu. This model was finetuned from unsloth/qwen2.5-coder-7b-instruct-bnb-4bit, leveraging Unsloth and Huggingface's TRL library for accelerated training. It is designed for general language tasks, building upon the capabilities of its base model with a focus on efficient development. The model has a context length of 32768 tokens.

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Model Overview

Developer-pintu/Qwen3.8-27B-bucket is a 7.6 billion parameter language model developed by Developer-pintu. It is finetuned from the unsloth/qwen2.5-coder-7b-instruct-bnb-4bit base model, indicating a potential specialization or enhancement for coding-related tasks, given the base model's name. The model was trained with a focus on efficiency, utilizing Unsloth and Huggingface's TRL library, which allowed for a 2x faster training process.

Key Characteristics

  • Base Architecture: Qwen2-based, building on a robust foundation.
  • Parameter Count: 7.6 billion parameters, offering a balance between performance and computational requirements.
  • Training Efficiency: Leveraged Unsloth and Huggingface's TRL library for significantly faster finetuning.
  • Context Length: Supports a substantial context window of 32768 tokens, enabling processing of longer inputs.
  • License: Released under the Apache-2.0 license, promoting open and flexible use.

Intended Use Cases

This model is suitable for a variety of general language understanding and generation tasks. Given its finetuning from a 'coder' base model, it may exhibit enhanced performance in:

  • Code generation and completion.
  • Code explanation and documentation.
  • General instruction-following tasks.
  • Applications requiring processing of longer text sequences due to its extended context length.