Bibliography (15):

1. Sustainable AI: Environmental Implications, Challenges and Opportunities

2. ​ ‘end-to-end’ directory

3. https://pytorch.org/blog/a-better-transformer-for-fast-transformer-encoder-inference/

4. Unsupervised Cross-lingual Representation Learning at Scale

5. General Purpose Text Embeddings from Pre-trained Language Models for Scalable Inference

6. MViT: Multiscale Vision Transformers

7. Masked Autoencoders As Spatiotemporal Learners

8. Introducing the AI Research SuperCluster—Facebook’s cutting-edge AI supercomputer for AI research

9. Muppet: Massive Multi-task Representations with Pre-Finetuning

10. Building Machine Translation Systems for the Next Thousand Languages

11. PIXEL: Language Modeling with Pixels

12. GrokNet: Unified Computer Vision Model Trunk and Embeddings For Commerce

13. Wikipedia Bibliography:

    1. https://en.wikipedia.org/wiki/Facebook  :

       https://en.wikipedia.org/wiki/Facebook

    2. Instagram

    3. https://en.wikipedia.org/wiki/Instagram#Reels  :

       https://en.wikipedia.org/wiki/Instagram#Reels