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Meta Llama 3 70B Instruct Fp8 by FriendliAI

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  8-bit   Autotrain compatible Base model:finetune:meta-llama... Base model:meta-llama/meta-lla...   Conversational   En   Facebook   Instruct   Llama   Llama-3   Meta   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/FriendliAI/Meta-Llama-3-70B-Instruct-fp8 

Meta Llama 3 70B Instruct Fp8 Benchmarks

LLME Score: 0.17999
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama 3 70B Instruct Fp8 (FriendliAI/Meta-Llama-3-70B-Instruct-fp8)

Meta Llama 3 70B Instruct Fp8 Parameters and Internals

Model Type 
text generation, instruction tuned
Use Cases 
Areas:
commercial, research
Applications:
assistant-like chat, natural language generation tasks
Primary Use Cases:
Dialogue systems, Assistant applications
Limitations:
Use prohibited beyond English and any manner violating applicable laws.
Considerations:
Requires safety testing and tuning for specific applications.
Supported Languages 
English ()
Training Details 
Data Sources:
publicly available online data
Data Volume:
15 trillion tokens
Methodology:
Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Context Length:
8000
Hardware Used:
Meta's Research SuperCluster, H100-80GB GPUs
Model Architecture:
Auto-regressive language model with optimized transformer architecture
Safety Evaluation 
Methodologies:
red-teaming, adversarial evaluations
Findings:
model carefully optimized for helpfulness and safety
Risk Categories:
Misinformation, Bias
Ethical Considerations:
Ethical issues are actively addressed during development.
Responsible Ai Considerations 
Fairness:
Model openly accessible with community contribution encouraged.
Transparency:
Active contributions to open consortiums like AI Alliance.
Accountability:
Efforts in place to limit misuse and support open community.
Mitigation Strategies:
Added safeguards like Meta Llama Guard 2 and Code Shield to mitigate risks.
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
Release Notes 
Date:
April 18, 2024
Notes:
Initial release of the instruction tuned models of Llama 3.
LLM NameMeta Llama 3 70B Instruct Fp8
Repository 🤗https://huggingface.co/FriendliAI/Meta-Llama-3-70B-Instruct-fp8 
Model NameLlama 3 70B Instruct
Model CreatorMeta Llama 3
Base Model(s)  Meta Llama 3 70B Instruct   meta-llama/Meta-Llama-3-70B-Instruct
Model Size70b
Required VRAM72.7 GB
Updated2025-02-22
MaintainerFriendliAI
Model Typellama
Instruction-BasedYes
Model Files  9.9 GB: 1-of-8   9.9 GB: 2-of-8   9.8 GB: 3-of-8   9.9 GB: 4-of-8   9.8 GB: 5-of-8   9.9 GB: 6-of-8   9.8 GB: 7-of-8   3.7 GB: 8-of-8
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than FriendliAI/Meta-Llama-3-70B-Instruct-fp8.

Rank the Meta Llama 3 70B Instruct Fp8 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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