Maswali yanayounganishwa na mwongozo · Kati Kiwango

Maswali ya Familia ya Mfano wa Llama

Kagua matoleo ya Llama ya uzani wazi, mstari wa mfano, kupanga maagizo, ufanisi wa uelekezaji, na anuwai mpya zaidi za moduli nyingi.

Njia za mwongozo zinazohusianaFamilia ya Mfano wa Llama
Swali 1 ya 8

How does Meta describe access to Llama model weights, and what governs use?

Hakiki kila swali8 maswali

Majibu na maelezo huonekana unapojibu maswali.

  1. How does Meta describe access to Llama model weights, and what governs use?
    • Weights are publicly released for eligible versions, subject to each version’s license and use terms
    • Every version is public domain with unrestricted use
    • Only Meta employees can access any Llama weights
    • The weights are downloadable without any terms
  2. Je, kifupi cha 'Llama' kinamaanisha nini?
    • Kujifunza kwa Linear na Usanifu wa Multimodal
    • Muundo Kubwa wa Lugha Meta AI
    • Mantiki ya Tabaka na Uchambuzi wa Mashine
    • Maombi ya Usimamizi wa Lugha ya Ndani
  3. Ni toleo gani la Llama liliongeza leseni inayoruhusu matumizi mapana ya kibiashara?
    • Llama ya asili 1
    • Llama 405 pekee
    • Lama 2
    • Hakuna hata mmoja wao anayeruhusu matumizi ya kibiashara
  4. Ni usanifu gani unaozingatia mifano ya Llama?
    • Kiainishi cha taswira cha kubadilisha
    • Mkusanyiko wa mti wa maamuzi
    • Mtandao unaorudiwa bila umakini
    • Transfoma ya dekoda pekee inayotabiri tokeni inayofuata
  5. Llama 'chat' au vibadala vilivyosanifiwa na maagizo hufanywaje ili kufuata madokezo ya mtumiaji?
    • Kupitia urekebishaji mzuri unaosimamiwa na mafunzo ya uimarishaji kutoka kwa maoni ya wanadamu
    • Kwa kuongeza azimio la skrini
    • Kwa kufuta mfano wa msingi kabisa
    • Kwa kutafsiri vidokezo vyote kwa Kilatini kwanza
  6. In what deployment setup can running Llama locally avoid sending prompts to a hosted inference service?
    • Whenever a model is downloaded, even when an app sends prompts to cloud tools
    • When inference runs on-device or on a private local server without a prompt-forwarding service
    • Only when the model is fine-tuned rather than used for inference
    • When the application stores prompts in a shared hosted API
  7. Which attention design did Meta adopt in Llama 3 8B and 70B to improve inference efficiency?
    • Residual vector quantization
    • Spatially-adaptive normalization
    • Grouped-query attention (GQA)
    • A recurrent state-space scan
  8. What inputs can Llama 3.2 Vision models accept?
    • Audio waveforms only
    • Video frames only, with no text
    • Sensor data without language or images
    • Text and images