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Meta Llama 3 70B Instruct GPTQ Int4 by study-hjt

 »  All LLMs  »  study-hjt  »  Meta Llama 3 70B Instruct GPTQ Int4   URL Share it on

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Model Card on HF 🤗: https://huggingface.co/study-hjt/Meta-Llama-3-70B-Instruct-GPTQ-Int4 

Meta Llama 3 70B Instruct GPTQ Int4 Benchmarks

LLME Score: 0.18474
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 GPTQ Int4 (study-hjt/Meta-Llama-3-70B-Instruct-GPTQ-Int4)

Meta Llama 3 70B Instruct GPTQ Int4 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Commercial, Research
Applications:
Assistant-like chat, Natural language generation
Primary Use Cases:
English language generation tasks
Limitations:
Use in languages other than English without proper fine-tuning, Use that violates applicable laws
Considerations:
Considerations for tailored safety testing for specific applications
Additional Notes 
Llama 3 supports only English language generation outright. Developers may fine-tune it to support additional languages.
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, optimized transformer architecture
Safety Evaluation 
Methodologies:
Red teaming, Adversarial evaluations
Findings:
Reduction of residual risks, Model refusal mitigation
Risk Categories:
CBRNE, Cybersecurity, Child Safety
Ethical Considerations:
Ethical guidelines for responsible AI deployment outlined
Responsible Ai Considerations 
Transparency:
An open approach to AI for better product safety and innovation
Mitigation Strategies:
Updated Responsible Use Guide, Meta Llama Guard 2, Code Shield
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Text and code generation
LLM NameMeta Llama 3 70B Instruct GPTQ Int4
Repository 🤗https://huggingface.co/study-hjt/Meta-Llama-3-70B-Instruct-GPTQ-Int4 
Base Model(s)  ...a Llama 3 70B Instruct Ov Int4   fakezeta/Meta-Llama-3-70B-Instruct-ov-int4
Model Size70b
Required VRAM39.8 GB
Updated2025-02-05
Maintainerstudy-hjt
Model Typellama
Instruction-BasedYes
Model Files  10.0 GB: 1-of-4   10.0 GB: 2-of-4   9.9 GB: 3-of-4   9.9 GB: 4-of-4
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
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-GPTQ-Int4.

Rank the Meta Llama 3 70B Instruct GPTQ Int4 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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