Language Models
GLM
Introduced by Zeng et al. in GLM-130B: An Open Bilingual Pre-trained ModelGLM is a bilingual (English and Chinese) pre-trained transformer-based language model that follow the traditional architecture of decoder-only autoregressive language modeling. It leverages autoregressive blank infilling as its training objective.
Source: GLM-130B: An Open Bilingual Pre-trained Model
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Language Modelling | 6 | 14.63% |
| Quantization | 3 | 7.32% |
| Question Answering | 2 | 4.88% |
| Denoising | 2 | 4.88% |
| Large Language Model | 2 | 4.88% |
| Semantic Segmentation | 2 | 4.88% |
| Dialogue Generation | 1 | 2.44% |
| Chatbot | 1 | 2.44% |
| Knowledge Graphs | 1 | 2.44% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
