Llama2 Chat 7B W4 by lmdeploy

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  Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us

Llama2 Chat 7B W4 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama2 Chat 7B W4 (lmdeploy/llama2-chat-7b-w4)
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Llama2 Chat 7B W4 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research, Interactive AI
Primary Use Cases:
AI assistant terminal interactions, Web UI interactions with Gradio
Considerations:
Requires NVIDIA GPU with sm80 minimum for inference.
Training Details 
Methodology:
Model weight quantization using AWQ algorithm.
Context Length:
2048
Model Architecture:
LLM with 4-bit weight quantization
Input Output 
Accepted Modalities:
text
Output Format:
Tokens generated in response to prompts
Performance Tips:
Ensure installation of lmdeploy v0.0.4 or above and use NVIDIA GPU sm80 or better.
LLM NameLlama2 Chat 7B W4
Repository ๐Ÿค—https://huggingface.co/lmdeploy/llama2-chat-7b-w4 
Model Size7b
Required VRAM3.9 GB
Updated2025-08-20
Maintainerlmdeploy
Model Typellama
Model Files  3.9 GB
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length2048
Model Max Length2048
Transformers Version4.31.0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than lmdeploy/llama2-chat-7b-w4.

Rank the Llama2 Chat 7B W4 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124