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Fireball Alpaca Llama3.1.08 8B Philos C R1 by EpistemeAI2

 »  All LLMs  »  EpistemeAI2  »  Fireball Alpaca Llama3.1.08 8B Philos C R1   URL Share it on

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  Autotrain compatible Base model:epistemeai2/firebal... Base model:finetune:epistemeai...   Conversational   En   Endpoints compatible   Llama   Model-index   Pytorch   Region:us   Sharded   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/EpistemeAI2/Fireball-Alpaca-Llama3.1.08-8B-Philos-C-R1 

Fireball Alpaca Llama3.1.08 8B Philos C R1 Benchmarks

MMLU Pro: 28.03
GPQA: 6.26
MUSR: 8.45
BBH: 26.76
IFEval: 53.16 vs 88 (so35)-39.6%
MATH Lvl 5: 12.39
LLME Score: 0.24117
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Fireball Alpaca Llama3.1.08 8B Philos C R1 (EpistemeAI2/Fireball-Alpaca-Llama3.1.08-8B-Philos-C-R1)
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Fireball Alpaca Llama3.1.08 8B Philos C R1 Parameters and Internals

Model Type 
text generation, multilingual dialogue
Use Cases 
Areas:
commercial applications, research
Applications:
assistant-like chat, natural language generation
Primary Use Cases:
multilingual dialogue, synthetic data generation, distillation
Limitations:
not suitable for unsupported languages without fine-tuning
Considerations:
Developers are encouraged to tailor safety measures for specific applications.
Additional Notes 
Tested for robustness in multiple use cases, including adversarial prompts.
Supported Languages 
English (Full Support), German (Full Support), French (Full Support), Italian (Full Support), Portuguese (Full Support), Hindi (Full Support), Spanish (Full Support), Thai (Full Support)
Training Details 
Data Sources:
publicly available online data
Data Volume:
15T+ tokens
Methodology:
Supervised fine-tuning with reinforcement learning from human feedback
Context Length:
128000
Model Architecture:
Optimized transformer architecture with Grouped-Query Attention
Responsible Ai Considerations 
Transparency:
Llama 3.1 models should be deployed with additional safety guardrails.
Accountability:
Developers are responsible for ensuring system safeguards in their applications.
Input Output 
Input Format:
`ChatML` prompt template
Accepted Modalities:
text
Output Format:
text and code
Release Notes 
Version:
3.1
Date:
July 23, 2024
Notes:
Model trained on offline dataset; future versions will focus on improved safety through community feedback.
LLM NameFireball Alpaca Llama3.1.08 8B Philos C R1
Repository 🤗https://huggingface.co/EpistemeAI2/Fireball-Alpaca-Llama3.1.08-8B-Philos-C-R1 
Base Model(s)  EpistemeAI2/Fireball-Alpaca-Llama3.1-8B-Philos   EpistemeAI2/Fireball-Alpaca-Llama3.1-8B-Philos
Model Size8b
Required VRAM16.1 GB
Updated2024-10-18
MaintainerEpistemeAI2
Model Typellama
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4
Supported Languagesen
Gated ModelYes
Model ArchitectureLlamaForCausalLM
Licenseproprietary
Context Length131072
Model Max Length131072
Transformers Version4.44.2
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|finetune_right_pad_id|>
Vocabulary Size128256
Torch Data Typefloat16

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Rank the Fireball Alpaca Llama3.1.08 8B Philos C R1 Capabilities

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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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