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Phind CodeLlama 34B V2 GGUF by TheBloke

 »  All LLMs  »  TheBloke  »  Phind CodeLlama 34B V2 GGUF   URL Share it on

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Base model:phind/phind-codella... Base model:quantized:phind/phi...   Code llama   Codegen   Gguf   Llama   Model-index   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/TheBloke/Phind-CodeLlama-34B-v2-GGUF 

Phind CodeLlama 34B V2 GGUF Benchmarks

LLME Score: 0.16286
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Phind CodeLlama 34B V2 GGUF (TheBloke/Phind-CodeLlama-34B-v2-GGUF)

Phind CodeLlama 34B V2 GGUF Parameters and Internals

Model Type 
llama
Use Cases 
Primary Use Cases:
Programming assistant
Limitations:
Limited safety testing
Supported Languages 
Python (proficient), C/C++ (proficient), TypeScript (proficient), Java (proficient), others (multi-lingual)
Training Details 
Data Sources:
proprietary dataset
Data Volume:
1.5B tokens
Methodology:
Instruction-tuning on Alpaca/Vicuna format, using DeepSpeed ZeRO 3 and Flash Attention 2
Context Length:
4096
Training Time:
15 hours
Hardware Used:
32 A100-80GB GPUs
Safety Evaluation 
Ethical Considerations:
This model has undergone very limited testing. Additional safety testing should be performed before any real-world deployments.
Input Output 
Input Format:
Alpaca/Vicuna instruction format
LLM NamePhind CodeLlama 34B V2 GGUF
Repository 🤗https://huggingface.co/TheBloke/Phind-CodeLlama-34B-v2-GGUF 
Model CreatorPhind
Base Model(s)  Phind CodeLlama 34B V2   Phind/Phind-CodeLlama-34B-v2
Model Size34b
Required VRAM14.2 GB
Updated2025-04-24
MaintainerTheBloke
Model Typellama
Model Files  14.2 GB   17.8 GB   16.3 GB   14.6 GB   19.1 GB   20.2 GB   19.1 GB   23.2 GB   23.8 GB   23.2 GB   27.7 GB   35.9 GB
GGUF QuantizationYes
Quantization Typegguf
Generates CodeYes
Model ArchitectureAutoModel
Licensellama2

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Phind-CodeLlama-34B-v2-GGUF.

Rank the Phind CodeLlama 34B V2 GGUF 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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