Luthfillah/lora_model_qwen3_kaggle_2_epoch
Luthfillah/lora_model_qwen3_kaggle_2_epoch is a 4 billion parameter Qwen3-based instruction-tuned language model developed by Luthfillah. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a context length of 40960 tokens, it is optimized for efficient performance derived from its accelerated training process.
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Model Overview
Luthfillah/lora_model_qwen3_kaggle_2_epoch is a 4 billion parameter instruction-tuned language model based on the Qwen3 architecture. Developed by Luthfillah, this model was fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit.
Key Characteristics
- Efficient Training: This model was trained significantly faster, achieving 2x speedup, by leveraging Unsloth and Huggingface's TRL library.
- Architecture: Built upon the Qwen3 foundation, known for its strong performance in various language understanding and generation tasks.
- Context Length: Supports a substantial context window of 40960 tokens, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.
Use Cases
This model is suitable for applications requiring a Qwen3-based instruction-tuned model with efficient training origins. Its accelerated fine-tuning process suggests potential for rapid deployment and iteration in development workflows.