Guide-yakabatana mibvunzo · Pakati Nhanho

Zhipu GLM Mibvunzo yeMienzaniso

Inovhara zita reGLM uye chinangwa chekudzidzisa, ChatGLM mutsara, yazvino modhi-yakatarwa kuburitswa, uye nekuchenjerera kududzira kwezvekugadzirisa kambani.

Nzira dzekutungamira dzinoenderanaZhipu Glm Models
Mubvunzo 1 ye 8

Chii chinonzi GLM mumhando dzeZhipu?

Tarisa mubvunzo wese8 mibvunzo

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

  1. Chii chinonzi GLM mumhando dzeZhipu?
    • General Mutauro Model
    • Global Learning Machine
    • Graphical Layer Model
    • Generative Logic Module
  2. Ndeipi yunivhesiti iyo Zhipu AI inonyanya kushamwaridzana nayo?
    • Peking University
    • Tsinghua University
    • MIT
    • Fudan University
  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. Chinangwa chekutanga cheGLM chinoshanda sei?
    • Iyo inovhara spans yemavara uye inozadza ma blanks autoregressively
    • Inongofanotaura izwi rinotevera chete
    • Inounganidza mazwi asina mavara
    • Inoisa mibairo yekutsvaga
  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
    • Kubvisa zvese zvekutarisisa
    • 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