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Frostwind 10.7B V1 by Sao10K

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  Autotrain compatible   En   Endpoints compatible   License:cc-by-nc-4.0   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/Sao10K/Frostwind-10.7B-v1 

Frostwind 10.7B V1 Benchmarks

ARC: 64.16 vs 96.7 (so35)-33.7%
HellaSwag: 85.38 vs 95.3 (gpt4)-10.4%
MMLU: 64.64 vs 88.3 (so35)-26.8%
TruthfulQA: 50.43 vs 59 (gpt4)-14.5%
WinoGrande: 83.74 vs 87.5 (gpt4)-4.3%
GSM8K: 52.16 vs 96.4 (so35)-45.9%
LLME Score: 0.27236
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Frostwind 10.7B V1 (Sao10K/Frostwind-10.7B-v1)
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Frostwind 10.7B V1 Parameters and Internals

LLM NameFrostwind 10.7B V1
Repository 🤗https://huggingface.co/Sao10K/Frostwind-10.7B-v1 
Model Size10.7b
Required VRAM21.4 GB
Updated2024-07-04
MaintainerSao10K
Model Typellama
Model Files  4.9 GB: 1-of-5   5.0 GB: 2-of-5   4.9 GB: 3-of-5   4.9 GB: 4-of-5   1.7 GB: 5-of-5
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensecc-by-nc-4.0
Context Length4096
Model Max Length4096
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

Quantized Models of the Frostwind 10.7B V1

Model
Likes
Downloads
VRAM
Frostwind 10.7B V1 EXL21510 GB
Frostwind 10.7B V1 GGUF44884 GB
Frostwind 10.7B V1 GPTQ266 GB
Frostwind 10.7B V1 AWQ1106 GB

Best Alternatives to Frostwind 10.7B V1

Best Alternatives
Context / RAM
Downloads
Likes
SOLAR 10.7B Instruct V1.0 128K128K / 21.4 GB54
SOLAR 10.7B V1.0 Instruct 16K16K / 21.4 GB632
SOLAR 10.7B V1.0 Base 16K16K / 21.4 GB690
SauerkrautLM SOLAR Instruct8K / 21.4 GB96846
PiVoT SOLAR 10.7B RP8K / 21.4 GB17807
MetaModelv28K / 21.4 GB19120
Fimbulvetr V2 Kuro Lotus Bf168K / 21.5 GB73
Kazemi 1.2 Solar8K / 21.4 GB00
Bucharest 0.25K / 21.4 GB91
SOLAR 10.7B Instruct V1.04K / 21.4 GB33744639
Note: green Score (e.g. "73.2") means that the model is better than Sao10K/Frostwind-10.7B-v1.

Rank the Frostwind 10.7B V1 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 v20241124
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