kairawal/Qwen3-4B-ES-SynthDolly-r16alpha32-E3-S73

TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:May 14, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The kairawal/Qwen3-4B-ES-SynthDolly-r16alpha32-E3-S73 is a 4 billion parameter Qwen3-based causal language model developed by kairawal, fine-tuned from unsloth/qwen3-4b. This model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. With a 32768 token context length, it is optimized for specific tasks through its fine-tuning process.

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Model Overview

The kairawal/Qwen3-4B-ES-SynthDolly-r16alpha32-E3-S73 is a 4 billion parameter language model based on the Qwen3 architecture. Developed by kairawal, this model was fine-tuned from the unsloth/qwen3-4b base model.

Key Characteristics

  • Architecture: Qwen3-based, 4 billion parameters.
  • Training Method: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • Context Length: Supports a context window of 32768 tokens.
  • License: Distributed under the Apache-2.0 license.

Potential Use Cases

This model is suitable for applications requiring a compact yet capable language model, especially where the specific fine-tuning objectives (implied by "ES-SynthDolly") align with the task. Its efficient training with Unsloth suggests it could be a good candidate for further domain-specific adaptation or deployment in resource-constrained environments.