Pharia-1-LLM-7B-control
| Property | Value |
|---|---|
| Parameter Count | 7B |
| Context Window | 8,192 tokens |
| Architecture | Decoder-only Transformer |
| License | Open Aleph License |
| Languages | English, German, French, Spanish, Italian, Portuguese, Dutch |
What is Pharia-1-LLM-7B-control?
Pharia-1-LLM-7B-control is an advanced multilingual language model developed by Aleph-Alpha Research, specifically optimized for European languages with a focus on German, French, and Spanish. The model features 7 billion parameters and is engineered to deliver concise, length-controlled responses while maintaining competitive performance with other models in its class.
Implementation Details
The model utilizes a decoder-only transformer architecture with 27 layers, 36 attention heads, and grouped-query attention for efficient memory usage. It implements rotary position embeddings and features a vocabulary size of 128,000 tokens. The model was trained on 7.7T tokens of carefully curated multilingual data, with special emphasis on high-quality content for automotive and engineering applications.
- 27 transformer layers with 4608 hidden dimension size
- 36 attention heads with 128 head size
- 4 Key-Value heads for efficient processing
- 8,192 token context window
- Grouped-query attention mechanism for reduced memory consumption
Core Capabilities
- Multilingual text generation optimized for European languages
- Enhanced token efficiency compared to similar models
- Specialized performance in automotive and engineering domains
- Length-controlled response generation
- Support for multi-turn conversations
- Zero-shot task handling across multiple languages
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its optimized token efficiency in European languages and specialized capabilities in technical domains, particularly automotive and engineering. It features lower tokenizer fertility than comparable models, making it more cost-effective for inference.
Q: What are the recommended use cases?
The model is particularly well-suited for technical documentation, engineering applications, and multilingual content generation. It excels in scenarios requiring precise, length-controlled responses and can be effectively used for chatbots, content generation, and technical writing assistance in European languages.
