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MetaModelv2 by gagan3012

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  Autotrain compatible   Conversational   Endpoints compatible   Instruct   Llama   Merge   Metamodelv2   Region:us   Safetensors   Sharded   Tensorflow

MetaModelv2 Benchmarks

ARC: 71.08 vs 96.7 (so35)-26.5%
HellaSwag: 88.56 vs 95.3 (gpt4)-7.1%
MMLU: 66.29 vs 88.3 (so35)-24.9%
TruthfulQA: 71.94 vs 59 (gpt4)21.9%
WinoGrande: 83.11 vs 87.5 (gpt4)-5%
GSM8K: 64.44 vs 96.4 (so35)-33.2%
LLME Score: 0.19442
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

MetaModelv2 Parameters and Internals

Training Details 
Data Sources:
VAGOsolutions/SauerkrautLM-SOLAR-Instruct, kyujinpy/Sakura-SOLAR-Instruct
Methodology:
Hybrid and merge of models
LLM NameMetaModelv2
Repository 🤗https://huggingface.co/gagan3012/MetaModelv2 
Model Size10.7b
Required VRAM21.4 GB
Updated2024-11-21
Maintainergagan3012
Model Typellama
Instruction-BasedYes
Model Files  9.9 GB: 1-of-3   9.8 GB: 2-of-3   1.7 GB: 3-of-3
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.35.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16
MetaModelv2 (gagan3012/MetaModelv2)

Best Alternatives to MetaModelv2

Best Alternatives
Context / RAM
Downloads
Likes
SOLAR 10.7B Instruct V1.0 128K128K / 21.4 GB784
SOLAR 10.7B V1.0 Instruct 16K16K / 21.4 GB632
SauerkrautLM SOLAR Instruct8K / 21.4 GB79947
Kazemi 1.2 Solar8K / 21.4 GB00
SOLAR 10.7B Instruct V1.04K / 21.4 GB151224614
ConfigurableSOLAR 10.7B4K / 21.4 GB47572
...arbonVillain En 10.7B V2 Slerp4K / 21.4 GB127030
...auerkrautLM UNA SOLAR Instruct4K / 21.4 GB126726
...0.7B Instruct STOCK SOLAR Ties4K / 42.9 GB24460
...struct STOCK SOLAR Passthrough4K / 53.4 GB16850
Note: green Score (e.g. "73.2") means that the model is better than gagan3012/MetaModelv2.

Rank the MetaModelv2 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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 v20241110
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