longtermrisk/Qwen3-8B-ftjob-04383f830ba9
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:May 10, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The longtermrisk/Qwen3-8B-ftjob-04383f830ba9 is an 8 billion parameter Qwen3 model developed by longtermrisk, fine-tuned using Unsloth and Huggingface's TRL library. This model is optimized for faster training, leveraging Unsloth's efficiency. It is suitable for applications requiring a Qwen3 architecture with enhanced training speed.
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Model Overview
The longtermrisk/Qwen3-8B-ftjob-04383f830ba9 is an 8 billion parameter language model based on the Qwen3 architecture. Developed by longtermrisk, this model has been fine-tuned with a focus on training efficiency.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Qwen3-8B. - Training Efficiency: The fine-tuning process utilized Unsloth and Huggingface's TRL library, enabling training at twice the speed compared to standard methods.
- Parameter Count: Features 8 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a context window of 32768 tokens.
Use Cases
This model is particularly well-suited for developers and researchers looking for:
- Efficient Fine-tuning: Ideal for projects where rapid iteration and faster training cycles are critical.
- Qwen3-based Applications: Suitable for tasks that benefit from the Qwen3 architecture's capabilities.
- Resource-Optimized Deployment: Its 8B parameter size makes it a viable option for scenarios where larger models might be too computationally intensive.