zypchn/BehChat-v0.1
TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Mar 23, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
BehChat-v0.1 is an 8 billion parameter Qwen3-based causal language model developed by zypchn, fine-tuned for chat applications. This model leverages Unsloth and Huggingface's TRL library for accelerated training, offering a context length of 32768 tokens. It is designed for efficient deployment in conversational AI tasks, building upon the DeepSeek-R1-0528-Qwen3-8B architecture.
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BehChat-v0.1: An Efficiently Fine-tuned Qwen3 Model
BehChat-v0.1 is an 8 billion parameter language model developed by zypchn, fine-tuned from the unsloth/DeepSeek-R1-0528-Qwen3-8B base model. This iteration focuses on delivering a performant model for conversational AI applications.
Key Capabilities & Features
- Base Architecture: Built upon the robust Qwen3 architecture, providing strong foundational language understanding and generation capabilities.
- Efficient Training: Fine-tuned using Unsloth and Huggingface's TRL library, enabling significantly faster training times (2x speedup).
- Context Length: Supports a substantial context window of 32768 tokens, allowing for processing longer conversations and more complex inputs.
- License: Released under the Apache-2.0 license, promoting open and flexible use.
Good For
- Chatbot Development: Its fine-tuned nature and Qwen3 base make it suitable for building responsive and coherent conversational agents.
- Research & Experimentation: Developers can leverage its efficient training methodology for further fine-tuning or exploring new applications.
- Applications requiring a balance of performance and resource efficiency within an 8B parameter footprint.