Maswali yanayounganishwa na mwongozo · Kati Kiwango

Maswali ya Miundo ya Zhipu GLM

Inashughulikia jina na lengo la mafunzo la GLM, ukoo wa ChatGLM, matoleo ya sasa ya modeli mahususi, na tafsiri ya tahadhari ya masasisho ya kampuni.

Njia za mwongozo zinazohusianaMifano ya Zhipu Glm
Swali 1 ya 8

GLM inasimamia nini katika mifano ya Zhipu?

Hakiki kila swali8 maswali

Majibu na maelezo huonekana unapojibu maswali.

  1. GLM inasimamia nini katika mifano ya Zhipu?
    • Mfano wa Lugha ya Jumla
    • Mashine ya Kujifunza ya Ulimwenguni
    • Mfano wa Tabaka la Graphical
    • Moduli ya Mantiki ya Kuzalisha
  2. Ni chuo kikuu gani cha Zhipu AI kinachohusishwa kwa karibu nacho?
    • Chuo Kikuu cha Peking
    • Chuo Kikuu cha Tsinghua
    • MIT
    • Chuo Kikuu cha Fudan
  3. What did the ChatGLM-6B release make available to developers?
    • A video-only diffusion model
    • A proprietary API with no released model
    • A bilingual Chinese-English chatbot model with deployment options for local hardware
    • A database for image annotations
  4. What does CogVideoX generate from a text prompt?
    • A protein structure
    • A transaction graph
    • A speech transcript only
    • A video clip
  5. Je, lengo la awali la mafunzo ya GLM linafanya kazi vipi?
    • Hufunika safu za maandishi na kujaza nafasi zilizoachwa kiotomatiki
    • Inatabiri tu neno linalofuata
    • Inakusanya maneno bila lebo
    • Huorodhesha matokeo ya utafutaji
  6. What is a stable technical question to ask about a specific Zhipu GLM release?
    • Whether all GLM releases have identical limits
    • Which capabilities, license, and evaluation results are documented for that exact version
    • Whether the company name predicts model quality
    • Whether a single benchmark proves general superiority
  7. What deployment option does the ChatGLM-6B repository document for reducing memory requirements?
    • Increasing the model to 70 billion parameters
    • Kuondoa tabaka zote za umakini
    • Quantized inference configurations such as 4-bit loading
    • Training a new tokenizer at each request
  8. How does the original GLM paper describe positional information for infilling spans?
    • It uses no position information
    • It assigns each document one global position
    • It treats masked spans as image patches
    • It uses two-dimensional positions to represent text position and the infilling span