myfi/parser_model_ner_4.05
The myfi/parser_model_ner_4.05 is a 4 billion parameter instruction-tuned Qwen3 model developed by myfi, fine-tuned from unsloth/Qwen3-4B-Instruct-2507. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for natural language processing tasks, leveraging its 32768 token context length for robust performance.
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Model Overview
The myfi/parser_model_ner_4.05 is a 4 billion parameter Qwen3-based instruction-tuned model developed by myfi. It was fine-tuned from the unsloth/Qwen3-4B-Instruct-2507 base model, leveraging the Unsloth library and Huggingface's TRL for accelerated training, achieving a 2x speed improvement.
Key Characteristics
- Architecture: Qwen3, a causal language model.
- Parameter Count: 4 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, enabling processing of longer inputs and more complex tasks.
- Training Efficiency: Utilizes Unsloth for optimized and faster fine-tuning.
Potential Use Cases
This model is suitable for various natural language processing applications, particularly those benefiting from instruction-following capabilities and a large context window. Its efficient training process suggests a focus on practical deployment and fine-tuning for specific downstream tasks.