Definition
Open weights models have their trained model parameters publicly available for download, allowing anyone to run them locally or fine-tune them.
Open Weights vs Open Source: - Open weights: Parameters available - Open source: Parameters + training code + data - Many "open" models are weights-only
Benefits: - Run locally (privacy) - No API costs - Customization via fine-tuning - Research and experimentation - No vendor lock-in
Notable Open Weights Models: - Meta Llama 3 family - Mistral models - Qwen models - Gemma (Google) - Phi models (Microsoft)
Considerations: - Require compute to run - May have license restrictions - Large file sizes - Self-hosting complexity
Examples
Downloading Llama 3.1 70B to run on your own GPU cluster without sending data to external APIs.
Related Terms
AI models trained on massive text datasets that can understand and generate human-like text.
Adapting a pre-trained model to perform better on specific tasks using additional training.
Meta's open-source large language model family, enabling community AI development.
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