abvgkjhjh/fact_extractor_dev_1b
The abvgkjhjh/fact_extractor_dev_1b is a 4 billion parameter Qwen3-based instruction-tuned causal language model developed by abvgkjhjh. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is optimized for specific fact extraction tasks, leveraging its efficient training methodology and Qwen3 architecture.
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Model Overview
The abvgkjhjh/fact_extractor_dev_1b is a 4 billion parameter Qwen3-based instruction-tuned model developed by abvgkjhjh. It was fine-tuned from unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit using the Unsloth library and Huggingface's TRL library, which facilitated a 2x faster training process.
Key Characteristics
- Architecture: Qwen3-based causal language model.
- Parameter Count: 4 billion parameters.
- Context Length: Supports a context length of 32768 tokens.
- Training Efficiency: Leverages Unsloth for significantly faster fine-tuning.
- License: Distributed under the Apache-2.0 license.
Intended Use
This model is specifically designed for fact extraction tasks, benefiting from its instruction-tuned nature and efficient training. Its Qwen3 architecture and substantial context window make it suitable for processing and extracting information from longer texts.