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AIRIC The Mistral by ericpolewski

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  Autotrain compatible Dataset:garage-baind/open-plat... Dataset:ise-uiuc/magicoder-evo...   Dataset:open-orca/openorca   Dataset:tatsu-lab/alpaca   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ericpolewski/AIRIC-The-Mistral 

AIRIC The Mistral Benchmarks

ARC: 59.98 vs 96.7 (so35)-38%
HellaSwag: 82.98 vs 95.3 (gpt4)-12.9%
MMLU: 60.67 vs 88.3 (so35)-31.3%
TruthfulQA: 48.24 vs 59 (gpt4)-18.2%
WinoGrande: 76.95 vs 87.5 (gpt4)-12.1%
GSM8K: 30.86 vs 96.4 (so35)-68%
LLME Score: 0.16526
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
AIRIC The Mistral (ericpolewski/AIRIC-The-Mistral)
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AIRIC The Mistral Parameters and Internals

Model Type 
Instruct, Conversational
Use Cases 
Primary Use Cases:
Conversational Assistant, Chatbot Applications
Limitations:
It's important to remembers' phrases may be present.
Additional Notes 
Set the top_p to .98 for the most social responses.
Training Details 
Data Sources:
Open-Orca/OpenOrca, ise-uiuc/Magicoder-Evol-Instruct-110K, tatsu-lab/alpaca, garage-bAInd/Open-Platypus, AIRIC
Methodology:
Instruct model using Alpaca format
Training Time:
3 epochs
LLM NameAIRIC The Mistral
Repository 🤗https://huggingface.co/ericpolewski/AIRIC-The-Mistral 
Model Size7b
Required VRAM14.4 GB
Updated2025-06-15
Maintainerericpolewski
Model Typellama
Instruction-BasedYes
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than ericpolewski/AIRIC-The-Mistral.

Rank the AIRIC The Mistral 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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