didula-wso2/qwen3-8B_sftep2-bal_klge113sft_16bit_vllm

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jun 16, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The didula-wso2/qwen3-8B_sftep2-bal_klge113sft_16bit_vllm is an 8 billion parameter Qwen3-based language model developed by didula-wso2. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language tasks, leveraging its Qwen3 architecture and 32768 token context length.

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Model Overview

This model, didula-wso2/qwen3-8B_sftep2-bal_klge113sft_16bit_vllm, is an 8 billion parameter language model based on the Qwen3 architecture. It was developed by didula-wso2 and fine-tuned from the unsloth/Qwen3-8B base model.

Key Characteristics

  • Architecture: Qwen3-based, a causal language model.
  • Parameter Count: 8 billion parameters.
  • Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • Context Length: Supports a context length of 32768 tokens.
  • License: Distributed under the Apache-2.0 license.

Intended Use Cases

This model is suitable for a variety of general language generation and understanding tasks, benefiting from its Qwen3 foundation and optimized fine-tuning process. Its 32K context window allows for processing longer inputs and generating more coherent, extended responses.

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