Terisara/studenttext_PAD_val_test02_QWEN

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 23, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Terisara/studenttext_PAD_val_test02_QWEN is a 3.1 billion parameter Qwen2-based instruction-tuned causal language model developed by Terisara. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.

Loading preview...

Model Overview

Terisara/studenttext_PAD_val_test02_QWEN is a 3.1 billion parameter Qwen2-based instruction-tuned language model developed by Terisara. It was finetuned from unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit.

Key Characteristics

  • Efficient Training: This model was trained 2x faster by utilizing Unsloth and Huggingface's TRL library, highlighting an optimized approach to model development.
  • Base Model: Built upon the Qwen2 architecture, known for its strong performance in various language understanding and generation tasks.

Use Cases

This model is suitable for general instruction-following applications where a compact yet capable language model is required. Its efficient training process suggests it could be a good candidate for scenarios prioritizing faster iteration and deployment.

Finetunes
1 models