Language Models
OPT-IML
Introduced by Iyer et al. in OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of GeneralizationOPT-IML is a version of OPT fine-tuned on a large collection of 1500+ NLP tasks divided into various task categories.
Source: OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| In-Context Learning | 1 | 16.67% |
| Instruction Following | 1 | 16.67% |
| Language Modelling | 1 | 16.67% |
| Meta-Learning | 1 | 16.67% |
| Natural Language Inference | 1 | 16.67% |
| Question Answering | 1 | 16.67% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
