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Llama 3 70B Instruct Gradient 262K AWQ by starsy

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  Arxiv:2305.14233   Arxiv:2309.00071   Arxiv:2310.05209   Arxiv:2402.08268   4-bit   Autotrain compatible   Awq   Conversational   En   Endpoints compatible   Instruct   Llama   Llama-3   Meta   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/starsy/Llama-3-70B-Instruct-Gradient-262k-AWQ 

Llama 3 70B Instruct Gradient 262K AWQ Benchmarks

ARC: 66.81 vs 96.7 (so35)-30.9%
HellaSwag: 85.46 vs 95.3 (gpt4)-10.3%
MMLU: 76.37 vs 88.3 (so35)-13.5%
TruthfulQA: 53.73 vs 59 (gpt4)-8.9%
WinoGrande: 82.64 vs 87.5 (gpt4)-5.6%
GSM8K: 78.85 vs 96.4 (so35)-18.2%
LLME Score: 0.20058
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3 70B Instruct Gradient 262K AWQ (starsy/Llama-3-70B-Instruct-Gradient-262k-AWQ)

Llama 3 70B Instruct Gradient 262K AWQ Parameters and Internals

Model Type 
Text Generation
Use Cases 
Areas:
Commercial, Research
Primary Use Cases:
Chat Assistant
Limitations:
Inappropriate outside stated language use, Potential bias and inaccuracies
Considerations:
Fine-tuning may be required for other languages, ensure compliance with laws
Additional Notes 
Model trained on a static offline dataset, future versions might evolve with community feedback.
Supported Languages 
en (High)
Training Details 
Data Sources:
SlimPajama, UltraChat
Data Volume:
15 trillion tokens pretraining; 105M tokens stage training; 188M tokens all stages
Methodology:
SFT, RLHF
Context Length:
262000
Hardware Used:
NVIDIA L40S, Meta's Research SuperCluster
Model Architecture:
Auto-regressive language model using optimized transformer architecture
Responsible Ai Considerations 
Transparency:
Outlined in Responsible Use Guide
Accountability:
Developers are accountable and should implement safety measures
Mitigation Strategies:
Purple Llama solutions and Llama Guard for input/output safety filtering
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Text, code
Release Notes 
Version:
April 18, 2024
Notes:
Initial release
LLM NameLlama 3 70B Instruct Gradient 262K AWQ
Repository 🤗https://huggingface.co/starsy/Llama-3-70B-Instruct-Gradient-262k-AWQ 
Base Model(s)  ...a 3 70B Instruct Gradient 524K   gradientai/Llama-3-70B-Instruct-Gradient-524k
Model Size70b
Required VRAM39.9 GB
Updated2025-01-12
Maintainerstarsy
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
Licensellama3
Context Length262144
Model Max Length262144
Transformers Version4.40.2
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than starsy/Llama-3-70B-Instruct-Gradient-262k-AWQ.

Rank the Llama 3 70B Instruct Gradient 262K AWQ 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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Release v20241227
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