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Llama 30B Supercot by ausboss

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  Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/ausboss/llama-30b-supercot 

Llama 30B Supercot Benchmarks

ARC: 64.85 vs 96.7 (so35)-32.9%
HellaSwag: 85.08 vs 95.3 (gpt4)-10.7%
MMLU: 56.56 vs 88.3 (so35)-35.9%
TruthfulQA: 53.96 vs 59 (gpt4)-8.5%
WinoGrande: 80.03 vs 87.5 (gpt4)-8.5%
GSM8K: 11.9 vs 96.4 (so35)-87.7%
LLME Score: 0.12366
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 30B Supercot (ausboss/llama-30b-supercot)
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Llama 30B Supercot Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
research, commercial applications
Applications:
language generation, contextual text generation
Primary Use Cases:
structured text generation based on instructions
Additional Notes 
Merge the LLaMa model with SuperCOT-LoRA for enhanced contextual response generation.
Input Output 
Input Format:
Structured prompting format with instruction, input, and response sections.
Accepted Modalities:
text
Output Format:
Textual response based on provided instruction and context.
Performance Tips:
Use specific prompt suffixes to improve output quality.
LLM NameLlama 30B Supercot
Repository 🤗https://huggingface.co/ausboss/llama-30b-supercot 
Model Size30b
Required VRAM11.5 GB
Updated2025-08-18
Maintainerausboss
Model Typellama
Model Files  0.0 GB: 1-of-243   0.4 GB: 2-of-243   0.4 GB: 3-of-243   0.2 GB: 4-of-243   0.2 GB: 5-of-243   0.3 GB: 6-of-243   0.3 GB: 7-of-243   0.2 GB: 8-of-243   0.2 GB: 9-of-243   0.3 GB: 10-of-243   0.3 GB: 11-of-243   0.2 GB: 12-of-243   0.2 GB: 13-of-243   0.3 GB: 14-of-243   0.3 GB: 15-of-243   0.2 GB: 16-of-243   0.2 GB: 17-of-243   0.3 GB: 18-of-243   0.3 GB: 19-of-243   0.2 GB: 20-of-243   0.2 GB: 21-of-243   0.3 GB: 22-of-243   0.3 GB: 23-of-243   0.2 GB: 24-of-243   0.2 GB: 25-of-243   0.3 GB: 26-of-243   0.3 GB: 27-of-243   0.2 GB: 28-of-243   0.2 GB: 29-of-243   0.3 GB: 30-of-243   0.3 GB: 31-of-243   0.2 GB: 32-of-243   0.2 GB: 33-of-243   0.3 GB: 34-of-243   0.3 GB: 35-of-243   0.2 GB: 36-of-243   0.2 GB: 37-of-243   0.3 GB: 38-of-243   0.3 GB: 39-of-243   0.2 GB: 40-of-243   0.2 GB: 41-of-243   0.3 GB: 42-of-243   0.3 GB: 43-of-243   0.2 GB: 44-of-243   0.2 GB: 45-of-243   0.3 GB: 46-of-243
Model ArchitectureLlamaForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.28.0
Vocabulary Size32000
Torch Data Typefloat16

Quantized Models of the Llama 30B Supercot

Model
Likes
Downloads
VRAM
Llama 30B Supercot GGUF015213 GB
Llama 30B Supercot 4bit11316 GB

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Note: green Score (e.g. "73.2") means that the model is better than ausboss/llama-30b-supercot.

Rank the Llama 30B Supercot 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 v20241124
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