ESarp/Qwen3-4B-AttackTree-DPO
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 14, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
ESarp/Qwen3-4B-AttackTree-DPO is a 4 billion parameter Qwen3 model developed by ESarp, fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It features a 32768 token context length and is optimized for specific applications related to attack tree analysis.
Loading preview...
Model Overview
ESarp/Qwen3-4B-AttackTree-DPO is a 4 billion parameter Qwen3 model, developed by ESarp and fine-tuned from the unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit base model. This model leverages Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.
Key Capabilities
- Efficient Training: Utilizes Unsloth for significantly accelerated fine-tuning.
- Qwen3 Architecture: Based on the Qwen3 model family, providing a robust foundation.
- Extended Context: Supports a context length of 32768 tokens, suitable for processing longer inputs.
Good For
- Applications requiring a Qwen3-based model with efficient training.
- Use cases benefiting from a 4 billion parameter model with a large context window.
- Specific tasks related to attack tree analysis, given its fine-tuning focus.