issozi/qwen-0.5b-agentic-web
TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:0.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 17, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The issozi/qwen-0.5b-agentic-web is a 0.5 billion parameter Qwen2.5-based causal language model developed by issozi. Finetuned using Unsloth and Huggingface's TRL library, this model is optimized for efficient performance with a 32768 token context length. Its training methodology allows for faster fine-tuning, making it suitable for applications requiring rapid deployment and iteration.
Loading preview...
Overview
The issozi/qwen-0.5b-agentic-web is a 0.5 billion parameter language model, finetuned by issozi from the unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit base model. It leverages the Qwen2.5 architecture and boasts a substantial context length of 32768 tokens.
Key Capabilities
- Efficient Fine-tuning: This model was trained using Unsloth and Huggingface's TRL library, enabling a 2x faster fine-tuning process compared to standard methods.
- Qwen2.5 Architecture: Benefits from the robust capabilities of the Qwen2.5 model family.
- Extended Context Window: Supports a 32768 token context, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.
Good For
- Rapid Prototyping: Its efficient training process makes it ideal for developers needing to quickly iterate and deploy specialized language models.
- Resource-Constrained Environments: As a 0.5 billion parameter model, it offers a balance of performance and computational efficiency.
- Applications Requiring Long Context: Suitable for tasks that benefit from a large context window, such as summarization of lengthy documents or complex multi-turn conversations.