FinaPolat/RAISED_QWEN_8B_SFT
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Apr 15, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The FinaPolat/RAISED_QWEN_8B_SFT is an 8 billion parameter Qwen3-based causal language model, fine-tuned by FinaPolat. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. With a 32768 token context length, it is optimized for efficient and rapid fine-tuning applications.
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Model Overview
FinaPolat/RAISED_QWEN_8B_SFT is an 8 billion parameter language model based on the Qwen3 architecture, developed by FinaPolat. This model distinguishes itself through its training methodology, leveraging Unsloth and Huggingface's TRL library to achieve a 2x faster fine-tuning process compared to standard methods.
Key Characteristics
- Base Model: Qwen3-8B
- Parameter Count: 8 billion
- Context Length: 32768 tokens
- Training Efficiency: Utilizes Unsloth for significantly accelerated fine-tuning.
- License: Apache-2.0, allowing for broad usage and modification.
Use Cases
This model is particularly well-suited for developers and researchers looking to:
- Rapidly fine-tune a Qwen3-based model for specific downstream tasks.
- Experiment with efficient training techniques using Unsloth.
- Deploy a capable 8B parameter model with a generous context window for various language generation and understanding applications.