abvgkjhjh/fact_extractor_dev_2-1b
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Mar 26, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Warm
The abvgkjhjh/fact_extractor_dev_2-1b is a 4 billion parameter Qwen3 model developed by abvgkjhjh, fine-tuned from abvgkjhjh/fact_extractor_dev_1b. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a 32768 token context length, it is optimized for efficient fact extraction tasks.
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Model Overview
The abvgkjhjh/fact_extractor_dev_2-1b is a 4 billion parameter Qwen3 model developed by abvgkjhjh. It is a fine-tuned iteration, building upon the abvgkjhjh/fact_extractor_dev_1b base model. This version benefits from a 2x faster training process, achieved through the integration of Unsloth and Huggingface's TRL library.
Key Capabilities
- Efficient Fact Extraction: Designed and fine-tuned for tasks requiring the extraction of specific information.
- Optimized Training: Leverages Unsloth for significantly faster training times compared to standard methods.
- Large Context Window: Features a substantial 32768 token context length, allowing for processing of longer inputs relevant to fact extraction.
Ideal Use Cases
- Information Retrieval: Suitable for applications where precise data points need to be identified and extracted from text.
- Data Processing: Can be integrated into workflows requiring automated fact collection from various sources.
- Research and Analysis: Useful for quickly sifting through documents to pull out key facts or figures.