什么是 Eagle 7B？

Eagle 7B is trained on 1.1 Trillion Tokens across 100+ world languages (70% English, 15% multilang, 15% code). - Built on the RWKV-v5 architecture (a linear transformer with 10-100x+ lower inference cost) - Ranks as the world's greenest 7B model (per token) - Outperforms all 7B class models in multi-lingual benchmarks - Approaches Falcon (1.5T), LLaMA2 (2T), Mistral (>2T?) level of performance...

Eagle 7B 的上下文长度是多少？

Eagle 7B 的上下文窗口为 10,000 token。

Eagle 7B 是何时发布的？

Eagle 7B 于 2024年1月29日发布。其知识截止日期为 2024年1月31日。

RWKV v5: Eagle 7B

Name: RWKV v5: Eagle 7B
Author: Recursal

recursal/eagle-7b

模型权重

Eagle 7B is trained on 1.1 Trillion Tokens across 100+ world languages (70% English, 15% multilang, 15% code).

Built on the RWKV-v5 architecture (a linear transformer with 10-100x+ lower inference cost)
Ranks as the world's greenest 7B model (per token)
Outperforms all 7B class models in multi-lingual benchmarks
Approaches Falcon (1.5T), LLaMA2 (2T), Mistral (>2T?) level of performance in English evals
Trade blows with MPT-7B (1T) in English evals
All while being an "Attention-Free Transformer"

Eagle 7B models are provided for free, by Recursal.AI, for the beta period till end of March 2024

Find out more here

rnn

模态

上下文

10K

发布时间

2024年1月29日

知识截止日期

2024年1月

RWKV v5: Eagle 7B

RWKV v5: Eagle 7B

活动

探索更多模型

活动

常见问题

探索更多模型

更多模型，来自 recursal

常见问题

更多模型，来自 recursal