PS4Research/EVPdEf4TUz3pRa2u
TEXT GENERATIONPricing:Input $0.48 / Output $0.96Concurrent Unit Cost:1Model Size:14BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 26, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
PS4Research/EVPdEf4TUz3pRa2u is a 14 billion parameter Qwen3-based causal language model developed by PS4Research, fine-tuned from unsloth/Qwen3-14B-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general language tasks, leveraging its efficient training methodology.
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Model Overview
PS4Research/EVPdEf4TUz3pRa2u is a 14 billion parameter language model, fine-tuned by PS4Research. It is based on the Qwen3 architecture and was specifically fine-tuned from the unsloth/Qwen3-14B-bnb-4bit model.
Key Characteristics
- Efficient Training: This model was trained with Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
- Base Model: Built upon the Qwen3 architecture, known for its strong performance in various language understanding and generation tasks.
- Parameter Count: Features 14 billion parameters, offering a balance between performance and computational requirements.
Potential Use Cases
- General Language Generation: Suitable for a wide range of text generation tasks, including creative writing, summarization, and conversational AI.
- Research and Development: Can serve as a foundation for further fine-tuning or experimentation due to its efficient training and robust base architecture.
- Applications requiring Qwen3 capabilities: Leverages the inherent strengths of the Qwen3 model family for diverse NLP applications.