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Llama 2 70B Chat Hf by meta-llama

 »  All LLMs  »  meta-llama  »  Llama 2 70B Chat Hf   URL Share it on

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Model Card on HF 🤗: https://huggingface.co/meta-llama/Llama-2-70b-chat-hf 

Llama 2 70B Chat Hf Benchmarks

LMSys ELO: 1093 vs 1272 (so35)-14.1%
MMLU Pro: 15.92
GPQA: 1.9
MUSR: 3.48
BBH: 4.61
IFEval: 49.58 vs 88 (so35)-43.7%
ARC: 64.59 vs 96.7 (so35)-33.2%
HellaSwag: 85.88 vs 95.3 (gpt4)-9.9%
MMLU: 63.91 vs 88.3 (so35)-27.6%
TruthfulQA: 52.8 vs 59 (gpt4)-10.5%
WinoGrande: 80.51 vs 87.5 (gpt4)-8%
GSM8K: 26.69 vs 96.4 (so35)-72.3%
MATH Lvl 5: 0.98
LLME Score: 0.4219
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 2 70B Chat Hf (meta-llama/Llama-2-70b-chat-hf)

Llama 2 70B Chat Hf Parameters and Internals

Model Type 
Pretrained, Fine-tuned generative text models
Use Cases 
Areas:
Commercial, Research
Primary Use Cases:
Assistant-like chat, Natural language generation tasks
Limitations:
English only, Subject to Acceptable Use Policy, Potential for bias and inaccurate responses
Considerations:
Perform application-specific safety testing
Additional Notes 
Llama 2 70B uses Grouped-Query Attention (GQA) for improved inference scalability
Supported Languages 
English (Optimized for dialogue use cases)
Training Details 
Data Sources:
Publicly available online data
Data Volume:
2 trillion tokens
Methodology:
Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Context Length:
4096
Hardware Used:
A100-80GB GPUs
Model Architecture:
Auto-regressive language model with an optimized transformer architecture
Safety Evaluation 
Ethical Considerations:
Testing conducted mainly in English; potential for biased or objectionable responses; safety testing recommended before deployment
Responsible Ai Considerations 
Mitigation Strategies:
Safety testing and tuning before deployment
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Text
LLM NameLlama 2 70B Chat Hf
Repository 🤗https://huggingface.co/meta-llama/Llama-2-70b-chat-hf 
Model Size70b
Required VRAM138 GB
Updated2024-12-22
Maintainermeta-llama
Model Typellama
Model Files  9.8 GB: 1-of-15   9.8 GB: 2-of-15   10.0 GB: 3-of-15   9.8 GB: 4-of-15   9.8 GB: 5-of-15   9.8 GB: 6-of-15   10.0 GB: 7-of-15   9.8 GB: 8-of-15   9.8 GB: 9-of-15   9.8 GB: 10-of-15   10.0 GB: 11-of-15   9.8 GB: 12-of-15   9.8 GB: 13-of-15   9.5 GB: 14-of-15   0.5 GB: 15-of-15   9.8 GB: 1-of-15   9.8 GB: 2-of-15   10.0 GB: 3-of-15   9.8 GB: 4-of-15   9.8 GB: 5-of-15   9.8 GB: 6-of-15   10.0 GB: 7-of-15   9.8 GB: 8-of-15   9.8 GB: 9-of-15   9.8 GB: 10-of-15   10.0 GB: 11-of-15   9.8 GB: 12-of-15   9.8 GB: 13-of-15   9.5 GB: 14-of-15   0.5 GB: 15-of-15
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.31.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

Quantized Models of the Llama 2 70B Chat Hf

Model
Likes
Downloads
VRAM
Llama 2 70B Chat GGUF123848629 GB
Llama 2 70B Chat GPTQ260877035 GB
Llama 2 70B Chat AWQ23263836 GB
WizardLM 70B V1.0 GPTQ13436 GB
Llama2 70B Chat 4bit AWQ12736 GB
Llama 2 70B Chat GGML1613028 GB
Llama 2 70B Chat 4bit Japanese523 GB

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Note: green Score (e.g. "73.2") means that the model is better than meta-llama/Llama-2-70b-chat-hf.

Rank the Llama 2 70B Chat Hf 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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