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ARIA 70B V2 by Faradaylab

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ARIA 70B V2 is an open-source language model by Faradaylab. Features: 70b LLM, VRAM: 138GB, Context: 4K, License: llama2, HF Score: 61.9, LLM Explorer Score: 0.13, Arc: 62.1, HellaSwag: 85.7, MMLU: 63.5, TruthfulQA: 49.8, WinoGrande: 81.7, GSM8K: 28.8.

  Arxiv:2307.09288   Autotrain compatible   Code   Data   Education   En   Endpoints compatible   Facebook   Fr   Languages   Legal   Llama   Meta   Openassistant   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/Faradaylab/ARIA-70B-V2 

ARIA 70B V2 Benchmarks

ARC: 62.12 vs 96.7 (so35)-35.8%
HellaSwag: 85.68 vs 95.3 (gpt4)-10.1%
MMLU: 63.49 vs 88.3 (so35)-28.1%
TruthfulQA: 49.8 vs 59 (gpt4)-15.6%
WinoGrande: 81.69 vs 87.5 (gpt4)-6.6%
GSM8K: 28.81 vs 96.4 (so35)-70.1%
LLME Score: 0.12803
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
ARIA 70B V2 (Faradaylab/ARIA-70B-V2)
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ARIA 70B V2 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research, Commercial applications
Supported Languages 
FR (High Quality), EN (General Topics)
Training Details 
Data Sources:
Publicly available French sources
Data Volume:
50,000 tokens
Methodology:
Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Training Time:
2 Days
Hardware Used:
NVIDIA A10G, Amazon Cloud Sagemaker
Model Architecture:
Optimized transformer architecture
Safety Evaluation 
Ethical Considerations:
ARIA is a new technology that carries risks with use.
Input Output 
Input Format:
text only
Accepted Modalities:
text
Output Format:
text only
Performance Tips:
Rope scaling is not active by default; to activate, add a line of code at parameters.
LLM NameARIA 70B V2
Repository 🤗https://huggingface.co/Faradaylab/ARIA-70B-V2 
Model Size70b
Required VRAM138 GB
Updated2025-09-23
MaintainerFaradaylab
Model Typellama
Model Files  9.8 GB: 1-of-15   9.8 GB: 2-of-15   10.0 GB: 3-of-15   9.8 GB: 4-of-15   9.8 GB: 5-of-15   9.8 GB: 6-of-15   10.0 GB: 7-of-15   9.8 GB: 8-of-15   9.8 GB: 9-of-15   9.8 GB: 10-of-15   10.0 GB: 11-of-15   9.8 GB: 12-of-15   9.8 GB: 13-of-15   9.5 GB: 14-of-15   0.5 GB: 15-of-15
Supported Languagesfr en
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.31.0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

Quantized Models of the ARIA 70B V2

Model
Likes
Downloads
VRAM
ARIA 70B V2 GGUF38529 GB
ARIA 70B V2 GPTQ4735 GB
ARIA 70B V2 AWQ2536 GB

Best Alternatives to ARIA 70B V2

Best Alternatives
Context / RAM
Downloads
Likes
... Chat 1048K Chinese Llama3 70B1024K / 141.9 GB90695
... Chat 1048K Chinese Llama3 70B1024K / 141.9 GB79144
... 3 70B Instruct Gradient 1048K1024K / 141.9 GB13122
Llama3 Function Calling 1048K1024K / 141.9 GB61
...a 3 70B Instruct Gradient 524K512K / 141.9 GB1023
...a 3 70B Instruct Gradient 262K256K / 141.9 GB2256
...ama 3 70B Arimas Story RP V2.0256K / 141.1 GB303
...ama 3 70B Arimas Story RP V1.6256K / 141.2 GB130
...ama 3 70B Arimas Story RP V1.5256K / 141.2 GB73
Yi 70B 200K RPMerge Franken195K / 142.4 GB31
Note: green Score (e.g. "73.2") means that the model is better than Faradaylab/ARIA-70B-V2.

Rank the ARIA 70B V2 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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