quiz bu lëkkale ak tegtal · Diggante Niveau
Laajteb EleutherAI
Xoolaat xeetu làkk yu ubbeeku yu EleutherAI, setu done Pile, jumtukaayi jàngat, ak tànneefi architecture yu am solo yu melni RoPE.
Laaj 1 de 8
How did EleutherAI first bring together its research community?
Xoolaatal laaj bu nekk8 laaj
Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.
- How did EleutherAI first bring together its research community?
- As a Discord server for discussing GPT-3 and open language modeling
- Bi nga xamee ni ab sosete buy tàmbali ci Silicon Valley
- Laboratoire gëstu bu nguur gi
- As a university’s official AI department
- Luy 'Pile' bi?
- Produit chatbot buñu moomeel
- ab done bu ubbeeku bu 825GB ngir tàggat ay xeetu làkk
- Benn xeetu lalu reso neuronal
- Platform ordinatëru niir bu EleutherAI
- Ci yii, yan ci ñoom mooy xeetu làkku EleutherAI?
- BERT-Yaatu
- Llama-2
- GPT-NeoX-20B
- PALM
- Lan lañuy jëfandikoo ngir jàngat LM?
- Defar ay nataal ci mbind
- kompresse diisaayu model
- Royuwaayi dalal ni API web
- Benchmarking xeetu làkk ci liggéey yu bari
- Which organizations are named in EleutherAI’s retrospective as research supporters?
- CoreWeave and Google TPU Research Cloud
- Nvidia and the National Science Foundation only
- The U.S. Department of Energy and NASA
- Amazon and the European Space Agency
- Ban coppite ci mbootaay la EleutherAI amal ci 2023?
- OpenAI moo ko jëndoon
- Ñu ngi ko formalise ni daara buy def gëstu buy def te Yàlla tax
- Nekk na fond de couverture buy wut xaalis
- Dafa tëju lëmm
- Which positional method does the GPT-NeoX-20B paper describe using instead of learned absolute position embeddings?
- A separate learned embedding for every document
- A convolutional image-position map
- Rotary Positional Embeddings (RoPE)
- A random position permutation at each layer
- What architectural arrangement is highlighted as a GPT-NeoX-20B difference from GPT-3?
- The model replaces its Transformer with a decision tree
- Every layer removes the attention mechanism
- It uses only an encoder and no autoregressive decoder
- Attention and feed-forward layers can be computed in parallel