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Mixtral AI CyberTron Ultra by LeroyDyer

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  Autotrain compatible Base model:leroydyer/mixtral a...   Code   Conversational   Cyber-series Dataset:cognitivecomputations/... Dataset:databricks/databricks-... Dataset:gretelai/synthetic tex... Dataset:huggingfacetb/cosmoped... Dataset:ise-uiuc/magicoder-evo...   Dataset:meta-math/metamathqa Dataset:mwitiderrick/swahilipl...   Dataset:open-orca/openorca   Dataset:open-orca/slimorca Dataset:rogendo/english-swahil...   Dataset:swahili   Dataset:teknium/openhermes-2.5   Dataset:uonlp/culturax   Dataset:yahma/alpaca-cleaned   Doctor   En   Endpoints compatible   Farmer   Instruct   License:apache-2.0   Medical   Mega-series   Milestone   Mistral   Region:us   Role-play   Safetensors   Self-rag   Sharded   Spydazwebai   Tensorflow   Thinkingbot   Trl   Unsloth

Mixtral AI CyberTron Ultra Benchmarks

MMLU Pro: 20.73
GPQA: 5.7
MUSR: 10.3
BBH: 27.75
IFEval: 15.56 vs 88 (so35)-82.3%
ARC: 62.2 vs 96.7 (so35)-35.7%
HellaSwag: 82.08 vs 95.3 (gpt4)-13.9%
MMLU: 61.15 vs 88.3 (so35)-30.7%
TruthfulQA: 53.09 vs 59 (gpt4)-10%
WinoGrande: 79.01 vs 87.5 (gpt4)-9.7%
GSM8K: 42.61 vs 96.4 (so35)-55.8%
MATH Lvl 5: 0.83
LLME Score: 0.30919
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Mixtral AI CyberTron Ultra Parameters and Internals

Model Type 
text-generation-inference, fine-tuned
Use Cases 
Areas:
medical, farmer, doctor, Mega-Series, Cyber-Series, Role-Play, Self-Rag, ThinkingBot
Additional Notes 
The model is highly tuned for text generation, role-play, and can maintain personas. It is designed for strategic merging and tuning to maintain different capabilities separately.
Supported Languages 
en (Proficient)
Training Details 
Data Sources:
gretelai/synthetic_text_to_sql, HuggingFaceTB/cosmopedia, teknium/OpenHermes-2.5, Open-Orca/SlimOrca, Open-Orca/OpenOrca, cognitivecomputations/dolphin-coder, databricks/databricks-dolly-15k, yahma/alpaca-cleaned, uonlp/CulturaX, mwitiderrick/SwahiliPlatypus, Rogendo/English-Swahili-Sentence-Pairs, ise-uiuc/Magicoder-Evol-Instruct-110K, meta-math/MetaMathQA
Methodology:
fine-tuning, unsloth
Context Length:
32000
Input Output 
Accepted Modalities:
text
LLM NameMixtral AI CyberTron Ultra
Repository 🤗https://huggingface.co/LeroyDyer/Mixtral_AI_CyberTron_Ultra 
Base Model(s)  Mixtral AI CyberTron Ultra   LeroyDyer/Mixtral_AI_CyberTron_Ultra
Model Size7.2b
Required VRAM14.4 GB
Updated2024-07-04
MaintainerLeroyDyer
Model Typemistral
Instruction-BasedYes
Model Files  1.9 GB: 1-of-8   1.9 GB: 2-of-8   2.0 GB: 3-of-8   1.9 GB: 4-of-8   2.0 GB: 5-of-8   1.9 GB: 6-of-8   2.0 GB: 7-of-8   0.8 GB: 8-of-8
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16
Mixtral AI CyberTron Ultra (LeroyDyer/Mixtral_AI_CyberTron_Ultra)

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Rank the Mixtral AI CyberTron Ultra 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 v20241110
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