OpenR1-Qwen-7B-French
| Property | Value |
|---|---|
| Base Model | Qwen2.5-Instruct |
| Training Dataset | WiroAI/dolphin-r1-french |
| Maximum Sequence Length | 4096 tokens |
| Training Infrastructure | 8x A6000 ADA cluster |
| Training Duration | 5 days |
| Model URL | https://huggingface.co/WiroAI/OpenR1-Qwen-7B-French |
What is OpenR1-Qwen-7B-French?
OpenR1-Qwen-7B-French is a specialized French language model that addresses the challenge of improving AI performance in lower-resource languages. Built upon Qwen2.5-Instruct and fine-tuned on the WiroAI/dolphin-r1-french dataset, this model represents a significant step forward in French language AI capabilities.
Implementation Details
The model was trained for 2 epochs using a learning rate of 1e-5 and implements a cosine learning rate schedule with 10% warmup phase. The training process utilized an 8x A6000 ADA cluster over 5 days, optimizing for enhanced French language reasoning and generation capabilities.
- Advanced token generation capability up to 4096 tokens
- Improved French language reasoning compared to DeepSeek's models
- Specialized training focused on maintaining consistent French language output
- Optimized for extended context understanding and generation
Core Capabilities
- Enhanced French language reasoning and response generation
- Extended token generation capacity for comprehensive responses
- Improved contextual understanding in French
- Structured thought process with clear step-by-step reasoning
- Support for chat-based interactions through template system
Frequently Asked Questions
Q: What makes this model unique?
This model specifically addresses the challenge of French language AI processing, offering improved reasoning capabilities and consistent French language output compared to existing multilingual models. It's specifically designed to avoid defaulting to English or Chinese reasoning, which is a common issue in other models.
Q: What are the recommended use cases?
The model is particularly well-suited for applications requiring extended French language generation, complex reasoning tasks, and detailed explanations. It's optimized for scenarios requiring outputs of up to 4096 tokens and performs best when allowed to generate comprehensive responses without strict token limitations.
