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Python Code 33B AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq Base model:ajibawa-2023/python... Base model:quantized:ajibawa-2...   Code Dataset:ajibawa-2023/python-co...   En   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Python Code 33B AWQ Benchmarks

LLME Score: 0.15826
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Python Code 33B AWQ Parameters and Internals

Model Type
llama
Training Details
Data Sources:
ajibawa-2023/Python-Code-23k-ShareGPT
Methodology:DeepSpeed codebase was used for training.
Training Time:42 hours
Hardware Used:
Azure 4 x A100 80GB
LLM NamePython Code 33B AWQ
Repository 🤗https://huggingface.co/TheBloke/Python-Code-33B-AWQ 
Model NamePython Code 33B
Model CreatorFeynman Innovations
Base Model(s)  Python Code 33B   ajibawa-2023/Python-Code-33B
Model Size33b
Required VRAM17.6 GB
Updated2024-11-12
MaintainerTheBloke
Model Typellama
Model Files  10.0 GB: 1-of-2   7.6 GB: 2-of-2
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length2048
Model Max Length2048
Transformers Version4.35.0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16
Python Code 33B AWQ (TheBloke/Python-Code-33B-AWQ)

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Python-Code-33B-AWQ.

Rank the Python Code 33B AWQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Release v20241110
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