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Rwkv Raven 7B by RWKV

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  Autotrain compatible   Dataset:eleutherai/pile   Endpoints compatible   Pytorch   Region:us   Rwkv   Sharded
Model Card on HF 🤗: https://huggingface.co/RWKV/rwkv-raven-7b 

Rwkv Raven 7B Benchmarks

ARC: 39.42 vs 96.7 (so35)-59.2%
HellaSwag: 66.48 vs 95.3 (gpt4)-30.2%
MMLU: 23.64 vs 88.3 (so35)-73.2%
TruthfulQA: 38.56 vs 59 (gpt4)-34.6%
WinoGrande: 62.9 vs 87.5 (gpt4)-28.1%
GSM8K: 0.3 vs 96.4 (so35)-99.7%
LLME Score: 0.15912
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Rwkv Raven 7B (RWKV/rwkv-raven-7b)

Rwkv Raven 7B Parameters and Internals

Model Type 
RNN, Transformer
Additional Notes 
RWKV is an RNN with transformer-level LLM performance. It is designed for fast inference, VRAM efficiency, and 'infinite' context length. The model allows for free sentence embedding and fast training.
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
Performance Tips:
The 'Raven' models need to be prompted in a specific way. Learn more about that in the integration blog post.
LLM NameRwkv Raven 7B
Repository 🤗https://huggingface.co/RWKV/rwkv-raven-7b 
Model Size7b
Required VRAM30.4 GB
Updated2025-02-22
MaintainerRWKV
Model Typerwkv
Model Files  2.0 GB: 1-of-17   1.8 GB: 2-of-17   1.8 GB: 3-of-17   1.8 GB: 4-of-17   1.8 GB: 5-of-17   1.8 GB: 6-of-17   1.8 GB: 7-of-17   1.8 GB: 8-of-17   1.8 GB: 9-of-17   1.8 GB: 10-of-17   1.8 GB: 11-of-17   1.8 GB: 12-of-17   1.8 GB: 13-of-17   1.8 GB: 14-of-17   1.8 GB: 15-of-17   1.8 GB: 16-of-17   1.4 GB: 17-of-17
Model ArchitectureRwkvForCausalLM
Transformers Version4.29.0.dev0
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50277
Torch Data Typefloat32

Best Alternatives to Rwkv Raven 7B

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Context / RAM
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V5 EagleX 7B0K / 15 GB62
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V5 Eagle 7B 1 0T HF0K / 15 GB261
Rwkv 4 7B Pile0K / 30.4 GB21230
Note: green Score (e.g. "73.2") means that the model is better than RWKV/rwkv-raven-7b.

Rank the Rwkv Raven 7B Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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