vierren/Qwen3.5-9B-ALLSFTMKN-FINAL
VISIONConcurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 29, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The vierren/Qwen3.5-9B-ALLSFTMKN-FINAL is a 9 billion parameter language model developed by vierren, fine-tuned from alvinrifky/Qwen3.5-9B-AITF-CPT. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x speed improvement during its finetuning process. With a 32768 token context length, it is optimized for efficient and accelerated fine-tuning workflows.
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Model Overview
The vierren/Qwen3.5-9B-ALLSFTMKN-FINAL is a 9 billion parameter language model developed by vierren. It is a fine-tuned version of the alvinrifky/Qwen3.5-9B-AITF-CPT base model, operating under an Apache-2.0 license.
Key Characteristics
- Efficient Fine-tuning: This model distinguishes itself by being fine-tuned with Unsloth and Huggingface's TRL library, resulting in a reported 2x speed increase during the training process.
- Parameter Count: It features 9 billion parameters, placing it in a capable size class for various language tasks.
- Context Length: The model supports a substantial context length of 32768 tokens, allowing it to process and generate longer sequences of text.
Use Cases
This model is particularly well-suited for developers and researchers looking for:
- Accelerated Development: Its optimized fine-tuning process makes it a strong candidate for projects requiring rapid iteration and experimentation with custom datasets.
- General Language Tasks: Given its Qwen 3.5 base and 9B parameters, it can be applied to a wide range of natural language processing applications, including text generation, summarization, and question answering.
- Long Context Applications: The 32768 token context window is beneficial for tasks that require understanding and generating extensive documents or conversations.