Guide-linked quiz · Medium Level
Meta AI Quiz
Evaluate a specific Llama release, its terms and configuration, downloadable artifacts, hosted products and responsibilities of local operation.
Question 1 of 8
Which downloadable model family belongs to Meta’s model ecosystem?
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Answers and explanations appear as you take the quiz.
- Which downloadable model family belongs to Meta’s model ecosystem?
- Llama
- Claude
- Gemini
- Mistral
- Before using a downloadable Llama release, what should a team read?
- Only the family name on a blog post
- That release’s model card, license, acceptable-use terms and supported configuration
- A social post about a different checkpoint
- Only the hosting provider’s marketing page
- A benchmark on one Llama checkpoint is used to predict another size’s performance. What is the issue?
- All sizes and modalities behave identically
- Only hosted systems can be compared
- Results do not automatically generalize across releases and configurations
- Model cards cover only consumer assistants
- A team downloads Llama weights to run a model locally. What else may it need?
- Only a text editor
- A social-media account
- No other software or hardware
- Compatible architecture code, tokenizer, configuration and suitable hardware
- A quantized community build is being considered for deployment. What should the team do?
- Evaluate that exact artifact directly
- Assume it behaves identically to Meta’s original checkpoint
- Use the base model card as proof of identical results
- Skip tests because weights are downloadable
- What does a downloadable checkpoint establish about reuse permissions?
- That all uses are unrestricted
- Nothing by itself; check the specific license and acceptable-use terms
- That all training data are public
- That the deployment has no risks
- How can a hosted assistant differ from a downloaded checkpoint?
- It is necessarily the same system with no added components
- It never uses tools or policies
- A product may add tools, policies and other components around a related model
- It cannot be evaluated on representative tasks
- Who must plan infrastructure, security, updates and monitoring for a local model deployment?
- The weights themselves
- The model’s training-data publishers
- Only users who enter prompts
- The organization operating the deployment
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