ms122222/mein_qwen_14b_merged

TEXT GENERATIONPricing:Input $0.48 / Output $0.96Concurrent Unit Cost:1Model Size:14BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 13, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The ms122222/mein_qwen_14b_merged is a 14 billion parameter Qwen3-based causal language model, developed by ms122222 and finetuned from huihui-ai/Huihui-Qwen3-14B-abliterated-v2. This model was trained using Unsloth and Huggingface's TRL library, enabling a 2x faster finetuning process. It offers a context length of 32768 tokens, making it suitable for applications requiring efficient processing of longer sequences.

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Overview

The ms122222/mein_qwen_14b_merged is a 14 billion parameter language model based on the Qwen3 architecture. Developed by ms122222, this model was finetuned from huihui-ai/Huihui-Qwen3-14B-abliterated-v2.

Key Characteristics

  • Architecture: Qwen3-based causal language model.
  • Parameter Count: 14 billion parameters.
  • Context Length: Supports a substantial context window of 32768 tokens.
  • Training Efficiency: Finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • License: Distributed under the Apache-2.0 license.

Use Cases

This model is particularly well-suited for developers looking for a Qwen3-based model that benefits from optimized finetuning techniques. Its efficient training process suggests potential for rapid iteration and deployment in various NLP tasks, especially those requiring a large context window.