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ReMask 3B by euclaise

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  Arxiv:2401.01335   Arxiv:2403.02178   Autotrain compatible   Conversational Dataset:euclaise/reddit-instru...   Dataset:euclaise/tinycot   Dataset:sablo/oasst2 curated   En   Endpoints compatible   Instruct   Region:us   Safetensors   Sharded   Stablelm   Tensorflow

ReMask 3B Benchmarks

MMLU Pro: 3.97
GPQA: 2.24
MUSR: 2.66
BBH: 8.74
IFEval: 24.19 vs 88 (so35)-72.5%
ARC: 43.77 vs 96.7 (so35)-54.7%
HellaSwag: 75.7 vs 95.3 (gpt4)-20.6%
MMLU: 41.82 vs 88.3 (so35)-52.6%
TruthfulQA: 42.13 vs 59 (gpt4)-28.6%
WinoGrande: 66.38 vs 87.5 (gpt4)-24.1%
GSM8K: 27.14 vs 96.4 (so35)-71.8%
MATH Lvl 5: 1.74
LLME Score: 0.26271
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

ReMask 3B Parameters and Internals

LLM NameReMask 3B
Repository 🤗https://huggingface.co/euclaise/ReMask-3B 
Model Size3b
Required VRAM11.2 GB
Updated2024-09-18
Maintainereuclaise
Model Typestablelm
Instruction-BasedYes
Model Files  5.0 GB: 1-of-3   5.0 GB: 2-of-3   1.2 GB: 3-of-3
Supported Languagesen
Model ArchitectureStableLmForCausalLM
Licensecc-by-sa-4.0
Context Length4096
Model Max Length4096
Transformers Version4.39.2
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50304
Torch Data Typefloat32
ReMask 3B (euclaise/ReMask-3B)

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Note: green Score (e.g. "73.2") means that the model is better than euclaise/ReMask-3B.

Rank the ReMask 3B 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 v2024072803
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