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Llama 65B 4bit by catid

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Llama 65B 4bit is an open-source language model by catid. Features: 65b LLM, VRAM: 34.7GB, Context: 2K, License: bsd-3-clause, Quantized, LLM Explorer Score: 0.07.

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

Llama 65B 4bit Benchmarks

LLME Score: 0.06875
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
Updated2026-04-01
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

Best Alternatives to Llama 65B 4bit

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...65B Gpt4 1.2 4bit 32g Actorder2K / 38.5 GB9130
....4.1 PI 8192 4bit 32g Actorder2K / 38.5 GB48
Enterredaas 65B 4bit 128g2K / 35.7 GB91
VicUnlocked Alpaca 65B 4bit2K / 35.7 GB76
LLaMA 65B 4bit 128g2K / 34.7 GB616
LLaMA 65B 4bit 32g2K / 38.5 GB710
Lite Oute 1 65M Instruct2K / 0.3 GB1712
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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