Awọn awoṣe Zhipu GLM adanwo

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

1. Kini GLM duro fun ni awọn awoṣe Zhipu?
   • Awoṣe Ede Gbogbogbo
   • Agbaye Learning Machine
   • Awoṣe Layer ayaworan
   • Generative kannaa Module
2. Ile-ẹkọ giga wo ni Zhipu AI ni ibatan julọ pẹlu?
   • Ile-ẹkọ giga Peking
   • Yunifasiti ti Tsinghua
   • MIT
   • Ile-ẹkọ giga 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. Bawo ni ipilẹṣẹ ikẹkọ GLM atilẹba ṣiṣẹ?
   • O boju-boju awọn ipari ti ọrọ ati ki o kun awọn ofifo laifọwọyi
   • O sọ asọtẹlẹ ọrọ ti o tẹle nikan
   • O ṣe akojọpọ awọn ọrọ laisi akole
   • O ṣe ipo awọn abajade wiwa
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
   • Yiyọ gbogbo akiyesi fẹlẹfẹlẹ
   • 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