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Meta Llama 3 70B Instruct AWQ by study-hjt

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Model Card on HF 🤗: https://huggingface.co/study-hjt/Meta-Llama-3-70B-Instruct-AWQ 

Meta Llama 3 70B Instruct AWQ Benchmarks

LLME Score: 0.19216
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 AWQ (study-hjt/Meta-Llama-3-70B-Instruct-AWQ)

Meta Llama 3 70B Instruct AWQ Parameters and Internals

Model Type 
large language model, instruction tuned, text generation
Use Cases 
Areas:
commercial, research
Applications:
assistant-like chat, natural language generation
Primary Use Cases:
Pretrained models for dialogue; Instruction tuned for specific applications.
Limitations:
Use outside English requires compliance with Acceptable Use Policy.
Considerations:
Use should align with the Llama 3 policies and guidelines.
Additional Notes 
Future versions will incorporate community feedback for model improvements.
Supported Languages 
English (fully supported; other languages may require fine-tuning)
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
Training Time:
7.7M GPU hours
Hardware Used:
H100-80GB GPUs
Model Architecture:
optimized transformer architecture
Safety Evaluation 
Methodologies:
red-teaming, adversarial evaluations
Findings:
reduced residual risks
Risk Categories:
child safety, cyber security
Ethical Considerations:
Limitations and misuses evaluated; developers encouraged to follow Responsible Use Guide.
Responsible Ai Considerations 
Fairness:
Designed to serve diverse backgrounds and perspectives.
Transparency:
Open approach to AI; community involvement encouraged.
Accountability:
Developers should perform safety testing before deployment.
Mitigation Strategies:
Use of Meta Llama Guard and Code Shield safeguards.
Input Output 
Input Format:
Text input only.
Accepted Modalities:
text
Output Format:
Generates text and code only.
LLM NameMeta Llama 3 70B Instruct AWQ
Repository 🤗https://huggingface.co/study-hjt/Meta-Llama-3-70B-Instruct-AWQ 
Base Model(s)  Meta Llama 3 120B Instruct   mlabonne/Meta-Llama-3-120B-Instruct
Model Size70b
Required VRAM39.9 GB
Updated2024-12-22
Maintainerstudy-hjt
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-9   4.9 GB: 2-of-9   4.9 GB: 3-of-9   4.9 GB: 4-of-9   4.9 GB: 5-of-9   4.9 GB: 6-of-9   4.9 GB: 7-of-9   3.4 GB: 8-of-9   2.1 GB: 9-of-9
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.39.3
Tokenizer ClassLlamaTokenizer
Padding Token<|end_of_text|>
Vocabulary Size128256
Torch Data Typefloat16

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

Rank the Meta Llama 3 70B Instruct AWQ 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 v20241217
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