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RA2.0 by Daemontatox

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  Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2-math-7b-...   Conversational   En   Endpoints compatible   Instruct   Model-index   Pytorch   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Daemontatox/RA2.0 

RA2.0 Benchmarks

MMLU Pro: 17.96
GPQA: 7.38
MUSR: 9.37
BBH: 28.47
IFEval: 37.84 vs 88 (so35)-57%
MATH Lvl 5: 33.91
LLME Score: 0.32159
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
RA2.0 (Daemontatox/RA2.0)

RA2.0 Parameters and Internals

LLM NameRA2.0
Repository 🤗https://huggingface.co/Daemontatox/RA2.0 
Base Model(s)  Qwen2 Math 7B Instruct   Qwen/Qwen2-Math-7B-Instruct
Model Size7b
Required VRAM15.2 GB
Updated2025-01-21
MaintainerDaemontatox
Model Typeqwen2
Instruction-BasedYes
Model Files  4.9 GB: 1-of-4   4.9 GB: 2-of-4   4.3 GB: 3-of-4   1.1 GB: 4-of-4   4.9 GB: 1-of-4   4.9 GB: 2-of-4   4.3 GB: 3-of-4   1.1 GB: 4-of-4
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.47.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

Best Alternatives to RA2.0

Best Alternatives
Context / RAM
Downloads
Likes
Rombos LLM V2.5 Qwen 7B128K / 15.2 GB74815
Rombo LLM V2.5 Qwen 7B128K / 15.2 GB311
Qwen2 7B Instruct V0.1128K / 15.2 GB409681
Cybertron V4 Qw7B UNAMGS128K / 15.2 GB1019
Gte Qwen2 7B Instruct128K / 30.5 GB41600245
Qwen2 7B Instruct V0.8128K / 15.2 GB409903
Model 3128K / 15.2 GB250
Cybertron V4 Qw7B MGS128K / 15.2 GB7512
...eCyberMix Qwen 2.5 7B Instruct128K / 15.2 GB382
Tsunami 0.5x 7B Instruct128K / 15.2 GB1611
Note: green Score (e.g. "73.2") means that the model is better than Daemontatox/RA2.0.

Rank the RA2.0 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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Release v20241227
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