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Starcoder2 15B AWQ by TechxGenus

 »  All LLMs  »  TechxGenus  »  Starcoder2 15B AWQ   URL Share it on

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  Arxiv:2004.05150   Arxiv:2205.14135   Arxiv:2207.14255   Arxiv:2305.13245   4-bit   Autotrain compatible   Awq   Code Dataset:bigcode/the-stack-v2-t...   Endpoints compatible   Model-index   Quantized   Region:us   Safetensors   Sharded   Starcoder2   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TechxGenus/starcoder2-15b-AWQ 

Starcoder2 15B AWQ Benchmarks

ARC: 47.35 vs 96.7 (so35)-51%
HellaSwag: 64.09 vs 95.3 (gpt4)-32.7%
MMLU: 51.35 vs 88.3 (so35)-41.8%
TruthfulQA: 37.87 vs 59 (gpt4)-35.8%
WinoGrande: 63.85 vs 87.5 (gpt4)-27%
GSM8K: 52.24 vs 96.4 (so35)-45.8%
HumanEvalA: 34.85
Python Eva: 44.15 vs 92 (so35)-52%
Java Eval: 33.86
Javascript: 44.24
CPP Eval: 41.44
PHP Eval: 39.48
Julia Eval: 33.19
D Eval: 23.64
Lua Eval: 43.75
R Eval: 19.81
Racket Eva: 22.41
Rust Eval: 38.03
Swift Eval: 34.18
LLME Score: 0.17203
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Starcoder2 15B AWQ (TechxGenus/starcoder2-15b-AWQ)
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Starcoder2 15B AWQ Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
text generation from code
Limitations:
Generated code may be inefficient, contain bugs or exploits.
Training Details 
Data Sources:
The Stack v2, GitHub, Arxiv, Wikipedia
Data Volume:
4+ trillion tokens
Methodology:
Grouped Query Attention, sliding window attention, Fill-in-the-Middle objective
Context Length:
16384
Hardware Used:
NVIDIA Eos Supercomputer, NVIDIA DGX H100
Model Architecture:
Transformer decoder
Input Output 
Input Format:
Python script or function snippets
Accepted Modalities:
text
Output Format:
Generated text or code snippets
LLM NameStarcoder2 15B AWQ
Repository 🤗https://huggingface.co/TechxGenus/starcoder2-15b-AWQ 
Base Model(s)  Starcoder2 15B   bigcode/starcoder2-15b
Model Size15b
Required VRAM9.2 GB
Updated2025-09-23
MaintainerTechxGenus
Model Typestarcoder2
Model Files  5.0 GB: 1-of-2   4.2 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureStarcoder2ForCausalLM
Licensebigcode-openrail-m
Context Length16384
Model Max Length16384
Transformers Version4.39.3
Tokenizer ClassGPT2Tokenizer
Vocabulary Size49152
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TechxGenus/starcoder2-15b-AWQ.

Rank the Starcoder2 15B AWQ 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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