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replicate/llama-7b
An implementation of Meta AI's original LLaMA-7B model, representing the most compact variant in the groundbreaking first-generation LLaMA family. LLaMA-7B demonstrated remarkable performance for its size by incorporating architectural optimizations and high-quality training data, establishing new efficiency benchmarks in language model development. The model features solid capabilities across various language tasks with particular strengths in reasoning, knowledge application, and context understanding. As a foundation model designed for research and further fine-tuning, LLaMA-7B provides an excellent starting point for developing specialized language applications with relatively modest computational requirements.
Technical Specifications:
- Developer: Meta AI (implemented by Replicate)
- Architecture: Optimized transformer for efficiency
- Parameters: 7 billion (smallest in original LLaMA family)
- Training Tokens: 1 trillion tokens
- Context Window: 2,048 tokens
- Training Optimization: Enhanced pre-training methodologies
- Resource Efficiency: Optimized for performance with lower compute
- Applications: Foundation for fine-tuning, research, specialized applications
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