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Llama 65B 4bit by catid

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  4bit   Autotrain compatible   Endpoints compatible   Llama   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/catid/llama-65b-4bit 

Llama 65B 4bit Benchmarks

LLME Score: 0.07955
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 65B 4bit (catid/llama-65b-4bit)
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Llama 65B 4bit Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research, Commercial Applications
Additional Notes 
This model implementation is based on the GPTQ approach and is compatible with 4-bit quantization, allowing efficiency in inference with reduced precision.
Input Output 
Input Format:
Text
Accepted Modalities:
text
Output Format:
Text
LLM NameLlama 65B 4bit
Repository 🤗https://huggingface.co/catid/llama-65b-4bit 
Model Size65b
Required VRAM34.7 GB
Updated2025-09-13
Maintainercatid
Model Typellama
Model Files  34.7 GB
Quantization Type4bit
Model ArchitectureLlamaForCausalLM
Licensebsd-3-clause
Context Length2048
Model Max Length2048
Transformers Version4.29.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Enterredaas 65B 4bit 128g2K / 35.7 GB21
VicUnlocked Alpaca 65B 4bit2K / 35.7 GB86
LLaMA 65B 4bit 128g2K / 34.7 GB1216
LLaMA 65B 4bit 32g2K / 38.5 GB1010
Lite Oute 1 65M2K / 0.3 GB439
Note: green Score (e.g. "73.2") means that the model is better than catid/llama-65b-4bit.

Rank the Llama 65B 4bit 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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