Awọn ile-iṣẹ Itọsọna

Awọn awoṣe Zhipu GLM

Zhipu AI jẹ ile-iṣẹ Beijing Tsinghua-spun lẹhin idile GLM (Awoṣe Ede Gbogbogbo).

Gbọ si itọsọna yiiAI-ṣe afihan · ~1 min

Lori iwe yi1 iseju kika
  1. Akopọ
  2. Jin Dive
  3. Real-World imuse
  4. Ọjọ iwaju ti Awọn awoṣe Zhipu GLM
  5. Fifi o sinu iwa
  6. Tesiwaju Ṣiṣawari
  7. Awọn ibeere ti a beere nigbagbogbo

Akopọ

It is a leading Chinese open-and-commercial model maker, pairing the ChatGLM lineage with multimodal and agent products.

Jin Dive

Zhipu AI’s GLM family spans language and multimodal models. The original GLM paper describes autoregressive blank infilling with two-dimensional positional information. The ChatGLM-6B paper and repository describe a bilingual Chinese-English dialogue model and quantized deployment options, with memory needs depending on configuration. CogVideoX is a text-to-video model; its technical paper details the video-generation architecture. Later GLM releases add capabilities and change licenses, so claims about hardware, modalities, and use rights must be checked against the exact release documentation.

Real-World imuse

Ṣiṣe ChatGLM ni agbegbe fun atilẹyin alabara ChatGLM kan ti ede Gẹẹsi-meji

Lilo CogVideoX lati ṣe ina awọn agekuru fidio kukuru lati awọn titẹ ọrọ

Ṣiṣe ohun elo Q&A iwe kan lori GLM-4 API fun awọn ipilẹ imọ ile-iṣẹ

Nbere CogVLM si akọle ati dahun awọn ibeere nipa awọn aworan ọja

Ọjọ iwaju ti Awọn awoṣe Zhipu GLM

Zhipu continues to release language, vision, and video models with different weights, capabilities, and licenses. Compare individual model cards and papers, and evaluate them on the intended hardware and workload rather than generalizing across releases.

Fifi o sinu iwa

Kini idi ti o ṣe pataki

  • Ilana olutaja. Awọn maapu opopona olutaja ni ipa kini awọn ẹya ti ẹgbẹ rẹ le kọ ni atẹle.
  • Iye owo ati isuna. Awọn ofin iṣowo ati awọn aṣayan imuṣiṣẹ ni ipa lori idiyele igba pipẹ ati eewu.
  • Ewu ati ailewu. Awọn imoriya ile-iṣẹ ṣe apẹrẹ awọn abawọn ọja, iduro ailewu, ati ṣiṣi.

Ṣọra fun

  • Awọn ikede ifilọlẹ le ju iduroṣinṣin lọ ni awọn iṣan-iṣẹ iṣelọpọ gidi.
  • Ifowoleri API tabi awọn iyipada eto imulo le fọ awọn arosinu ni alẹ.
  • Igbẹkẹle olutaja ẹyọkan ṣe alekun titiipa-inu ati awọn idiyele ijira.

Next awọn igbesẹ

  1. Ṣe ayẹwo awọn olupese nipa lilo awọn iṣẹ ṣiṣe tirẹ ati awọn ipilẹ data.
  2. Ṣe atunyẹwo asiri, aabo, ati awọn ofin ofin ṣaaju iṣọpọ.
  3. Ṣetọju eto ipadabọ kọja awọn awoṣe tabi awọn olutaja.
  4. Bojuto awọn akọsilẹ itusilẹ nitoribẹẹ awọn iyipada maapu oju-ọna ma ṣe iyalẹnu awọn ẹgbẹ.

Tesiwaju Ṣiṣawari

Ìwé ìròyìn ọfẹ

Gba ìkànìyàn AI ojoojúmọ́

Ìtàn AI mẹta tó jẹ́rìí ní gbogbo owurọ́ ọjọ́ iṣẹ́, kọ́wé ní Gẹ̀ẹ́sì tó rọrùn. Ọfẹ́ fún gbogbo àkókò, kò sí ìpolówó.

Ìmeèlì kan ní gbogbo ọjọ́ iṣẹ́. Yọkúrò ní ìkànìyàn ní ìkànìyàn kan. A kò ta tàbí pín àdírẹ́sì rẹ.

Ṣe idanwo fun ara rẹ

Take the Zhipu GLM Models quiz

Ìdáhùn lẹ́sẹ̀kẹsẹ̀ lórí gbogbo ìdáhùn, àti iwe-ẹ̀rí tó lè pin pẹ̀lú ID tó lè jẹ́rìí lẹ́yìn tí o bá kọ́ ẹ̀kọ́.

Bẹrẹ adanwo

Ṣe àtìlẹ́yìn ẹ̀kọ́ AI ọfẹ́. AI Understanding jẹ́ àjọ àìní èrè 501(c)(3) — kò sí ìpolówó, kò sí àkúnya owó, ní gbogbo àkókò. Ṣe ẹbun kan

Awọn ibeere ti a beere nigbagbogbo

What is Zhipu GLM Models?

Zhipu AI jẹ ile-iṣẹ Beijing Tsinghua-spun lẹhin idile GLM (Awoṣe Ede Gbogbogbo). O jẹ oluṣe awoṣe ṣiṣi-ati-owo ti Ilu Kannada ti o ṣaju, ti o somọ laini ChatGLM pẹlu multimodal ati awọn ọja aṣoju.

Kini GLM duro fun ni awọn awoṣe Zhipu?

GLM duro fun Awoṣe Ede Gbogbogbo, faaji ni ọkan ti tito sile Zhipu.

What did the ChatGLM-6B release make available to developers?

The ChatGLM-6B paper and repository describe a bilingual Chinese-English dialogue model and quantized deployment options; hardware needs depend on configuration.

What does CogVideoX generate from a text prompt?

The CogVideoX paper and project describe text-to-video generation.

Bawo ni ipilẹṣẹ ikẹkọ GLM atilẹba ṣiṣẹ?

GLM ṣe idapọ iran autoregressive pẹlu kikun-ofo, oye isokan ati iran ni awoṣe kan.

What is a stable technical question to ask about a specific Zhipu GLM release?

Zhipu’s model family changes across releases; check the documentation and evaluation for the specific model version.