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CodeLlama 70B Python AWQ by TheBloke

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  Arxiv:2308.12950   4-bit   Autotrain compatible   Awq Base model:codellama/codellama... Base model:quantized:codellama...   Code   Codegen   Llama   Llama2   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TheBloke/CodeLlama-70B-Python-AWQ 

CodeLlama 70B Python AWQ Benchmarks

LLME Score: 0.17268
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CodeLlama 70B Python AWQ (TheBloke/CodeLlama-70B-Python-AWQ)

CodeLlama 70B Python AWQ Parameters and Internals

Model Type 
llama
Use Cases 
Primary Use Cases:
Code synthesis, Python programming
Limitations:
Use in languages other than English is out-of-scope
Training Details 
Methodology:
AWQ - 4-bit low-bit weight quantization
Context Length:
16000
Hardware Used:
A100-80GB GPUs
Model Architecture:
Optimized transformer architecture
Input Output 
Input Format:
Text input
Accepted Modalities:
text
Output Format:
Text output
LLM NameCodeLlama 70B Python AWQ
Repository 🤗https://huggingface.co/TheBloke/CodeLlama-70B-Python-AWQ 
Model NameCodeLlama 70B Python
Model CreatorCode Llama
Base Model(s)  CodeLlama 70B Python Hf   codellama/CodeLlama-70b-Python-hf
Model Size70b
Required VRAM36.6 GB
Updated2024-12-22
MaintainerTheBloke
Model Typellama
Model Files  9.9 GB: 1-of-4   9.9 GB: 2-of-4   9.9 GB: 3-of-4   6.9 GB: 4-of-4
Supported Languagescode
AWQ QuantizationYes
Quantization Typeawq
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32016
Torch Data Typefloat16

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...odeLlama 70B Hf 2.4bpw H6 EXL216K / 21.3 GB91
...70B Instruct Nf4 Fp16 Upscaled4K / 138.7 GB4092
...Llama 70B Instruct Hf 4bit MLX4K / 39.1 GB2425
...deLlama 70B Python Hf 4bit MLX4K / 39.1 GB1111
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/CodeLlama-70B-Python-AWQ.

Rank the CodeLlama 70B Python AWQ 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 v20241217
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