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Rwkv 4 1b5 Pile by RWKV

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Rwkv 4 1b5 Pile is an open-source language model by RWKV. Features: LLM, VRAM: 6.1GB, HF Score: 33.3, LLM Explorer Score: 0.13, Arc: 31.8, HellaSwag: 52.3, MMLU: 25.8, TruthfulQA: 35.8, WinoGrande: 53.8.

  Dataset:eleutherai/pile   Endpoints compatible   Pytorch   Region:us   Rwkv
Model Card on HF 🤗: https://huggingface.co/RWKV/rwkv-4-1b5-pile 

Rwkv 4 1b5 Pile Benchmarks

ARC: 31.83 vs 96.7 (so35)-67.1%
HellaSwag: 52.25 vs 95.3 (gpt4)-45.2%
MMLU: 25.77 vs 88.3 (so35)-70.8%
TruthfulQA: 35.8 vs 59 (gpt4)-39.3%
WinoGrande: 53.83 vs 87.5 (gpt4)-38.5%
LLME Score: 0.12553
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Rwkv 4 1b5 Pile (RWKV/rwkv-4-1b5-pile)
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Rwkv 4 1b5 Pile Parameters and Internals

Model Type 
RNN, transformer-level, LLM
Training Details 
Data Sources:
EleutherAI/pile
Model Architecture:
RWKV is an RNN with transformer-level performance. It combines features of RNN and transformer architectures.
LLM NameRwkv 4 1b5 Pile
Repository 🤗https://huggingface.co/RWKV/rwkv-4-1b5-pile 
Required VRAM6.1 GB
Updated2026-04-02
MaintainerRWKV
Model Typerwkv
Model Files  6.1 GB
Model ArchitectureRwkvForCausalLM
Transformers Version4.29.0.dev0
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50277
Torch Data Typefloat32

Best Alternatives to Rwkv 4 1b5 Pile

Best Alternatives
Context / RAM
Downloads
Likes
Rwkv Raven 1b50K / 6.1 GB141212
EagleX 1 7T HF0K / 15 GB1410
... Pileplus 1B5 Evol Instruct V20K / 6.1 GB10400
...t 1B4 L94 D1024 Rwkv Converted0K / 5.3 GB70
Music 4 Rwkv Converted0K / 2.3 GB50
Rwkv Musenet Test Untrained40K / 0.9 GB60
Rwkv Musenet Test Untrained30K / 1.8 GB60
Rwkv Musenet Test Untrained0K / 0.1 GB60
Rwkv Music30K / 1.7 GB01
MuseRift0K / 1.7 GB60
Note: green Score (e.g. "73.2") means that the model is better than RWKV/rwkv-4-1b5-pile.

Rank the Rwkv 4 1b5 Pile Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
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