catchshubham/qwen3-14b-neet-finetuned-merged
The catchshubham/qwen3-14b-neet-finetuned-merged is a 14 billion parameter Qwen3 model developed by catchshubham. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is optimized for specific tasks through this efficient finetuning process, leveraging its 32768 token context length.
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Model Overview
The catchshubham/qwen3-14b-neet-finetuned-merged is a 14 billion parameter language model based on the Qwen3 architecture. Developed by catchshubham, this model was efficiently finetuned using the Unsloth library in conjunction with Huggingface's TRL library, which allowed for a 2x acceleration in the training process.
Key Characteristics
- Base Model: Qwen3-14B
- Developer: catchshubham
- Training Efficiency: Finetuned 2x faster using Unsloth and Huggingface TRL.
- Context Length: Supports a substantial 32768 token context window.
Use Cases
This model is suitable for applications requiring a Qwen3-14B base model that has undergone specialized finetuning. Its efficient training methodology suggests it could be a good candidate for tasks where rapid iteration and deployment of finetuned models are beneficial, leveraging its large context window for complex inputs.