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Model selection is a design decision shaped by the work you need to do. A broad leaderboard rank does not resolve every requirement of your application.
Write a short requirements brief
Define the task, expected languages, acceptable latency, privacy constraints and budget. State whether you need text, image, audio or tool-use capabilities. Identify the output and context requirements without assuming that a larger maximum is always useful.
Check the actual licence and deployment terms. Downloadable weights, an open repository and permission for your intended use are different things. Read the model card and relevant licence rather than relying on a label in a social post.
Compare on representative cases
Use a small task-specific evaluation before investing in a larger integration. Include an unsupported question, a difficult input and a case where the model should ask for clarification or decline an action.
Record quality, cost per successful task, latency and failure behaviour. If you add retrieval or tools, distinguish the base model's performance from the complete system's performance.
Plan for change
Model versions, availability and provider terms can change. Record the configuration you tested and define what would trigger reevaluation. Avoid making an application depend on an assumption you have never checked.
Discussion: Which requirement has ruled out an otherwise impressive model in your work?
Reference: Hugging Face model-card documentation.
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