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CodeLlama 13B Python Fp16 by TheBloke

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  Autotrain compatible   Codegen   Codellama   Custom code   Endpoints compatible   Fp16   Llama   Llama2   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TheBloke/CodeLlama-13B-Python-fp16 

CodeLlama 13B Python Fp16 Benchmarks

ARC: 33.19 vs 96.7 (so35)-65.7%
HellaSwag: 44.5 vs 95.3 (gpt4)-53.3%
MMLU: 25.94 vs 88.3 (so35)-70.6%
TruthfulQA: 43.99 vs 59 (gpt4)-25.4%
WinoGrande: 67.4 vs 87.5 (gpt4)-23%
GSM8K: 10.08 vs 96.4 (so35)-89.5%
LLME Score: 0.1971
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CodeLlama 13B Python Fp16 (TheBloke/CodeLlama-13B-Python-fp16)

CodeLlama 13B Python Fp16 Parameters and Internals

Model Type 
text generation, code synthesis
Use Cases 
Areas:
Commercial, Research
Applications:
Code synthesis, Code understanding, Python specific tasks
Primary Use Cases:
Commercial code generation, Research projects in programming and AI
Limitations:
Not for non-English languages, Should not violate laws or regulations
Considerations:
Adhere to legal compliances.
Additional Notes 
Intended for Python code tasks; requires specific handling for different operations.
Supported Languages 
English (proficient), Python (proficient)
Training Details 
Data Sources:
Same data as Llama 2 with different weights
Methodology:
Fine-tuned with additional instruction data for CodeLlama - Instruct
Context Length:
100000
Training Time:
January 2023 - July 2023
Hardware Used:
Meta’s Research Super Cluster, A100-80GB GPUs
Model Architecture:
Autoregressive language model using optimized transformer architectures
Responsible Ai Considerations 
Fairness:
Tested primarily in English.
Transparency:
Model's potential outputs cannot be predicted in advance.
Accountability:
Developers should perform safety testing and tuning tailored to their specific applications before deployment.
Mitigation Strategies:
Please see the Responsible Use Guide for more details.
Input Output 
Input Format:
Text only
Accepted Modalities:
text
Output Format:
Text only
Performance Tips:
Use 'trust_remote_code=True' for optimal operation due to a change in the RoPE Theta value
LLM NameCodeLlama 13B Python Fp16
Repository 🤗https://huggingface.co/TheBloke/CodeLlama-13B-Python-fp16 
Base Model(s)  CodeLlama 13B Python Hf   codellama/CodeLlama-13b-Python-hf
Model Size13b
Required VRAM26 GB
Updated2024-12-21
MaintainerTheBloke
Model Typellama
Model Files  9.9 GB: 1-of-3   9.9 GB: 2-of-3   6.2 GB: 3-of-3
Quantization Typefp16
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length16384
Model Max Length16384
Transformers Version4.32.0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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WhiteRabbitNeo 13B V116K / 26 GB1817404
CodeLlama 13B Instruct Fp1616K / 26 GB204629
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...Llama 13B Instruct Hf 4bit MLX16K / 7.8 GB802
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Trinity 13B 3.0bpw H6 EXL216K / 5.2 GB101
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/CodeLlama-13B-Python-fp16.

Rank the CodeLlama 13B Python Fp16 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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Release v20241217
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