jtatman/qwen_3_4b_mythos_finetune_16bit

TEXT GENERATIONConcurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jun 28, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The jtatman/qwen_3_4b_mythos_finetune_16bit is a 4 billion parameter Qwen3-based causal language model developed by jtatman, fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster finetuning. It offers a 32768 token context length, making it suitable for applications requiring efficient processing of longer sequences.

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Model Overview

The jtatman/qwen_3_4b_mythos_finetune_16bit is a 4 billion parameter language model based on the Qwen3 architecture, developed by jtatman. It was fine-tuned from the unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit model, leveraging the Unsloth library and Huggingface's TRL for accelerated training.

Key Characteristics

  • Base Model: Qwen3 architecture.
  • Parameter Count: 4 billion parameters.
  • Context Length: Supports a substantial context window of 32768 tokens.
  • Training Efficiency: Finetuned 2x faster using Unsloth, indicating optimized training processes.
  • License: Released under the Apache-2.0 license.

Use Cases

This model is particularly well-suited for applications where efficient finetuning and a large context window are beneficial. Its Qwen3 base and optimized training suggest potential for various natural language processing tasks, especially those requiring processing of extensive input texts.