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Starchat2 15B V0.1 AWQ by stelterlab

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Starchat2 15B V0.1 AWQ is an open-source language model by stelterlab. Features: 15b LLM, VRAM: 9.2GB, Context: 16K, License: bigcode-openrail-m, Quantized, LLM Explorer Score: 0.13.

  Arxiv:2311.07911   Arxiv:2402.19173   4-bit   Awq Base model:huggingfaceh4/starc... Base model:quantized:huggingfa...   Conversational Dataset:huggingfaceh4/orca dpo... Dataset:huggingfaceh4/ultrafee...   Endpoints compatible   Quantized   Region:us   Safetensors   Starcoder2
Model Card on HF 🤗: https://huggingface.co/stelterlab/starchat2-15b-v0.1-AWQ 

Starchat2 15B V0.1 AWQ Benchmarks

LLME Score: 0.13086
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Starchat2 15B V0.1 AWQ (stelterlab/starchat2-15b-v0.1-AWQ)
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Starchat2 15B V0.1 AWQ Parameters and Internals

Model Type 
GPT-like, fine-tuned
Use Cases 
Areas:
chat, programming
Applications:
coding assistant
Primary Use Cases:
code completion, programming help
Limitations:
syntactically valid but semantically incorrect code possible, demographic bias aligned with GitHub community, false URLs
Considerations:
Review output for accuracy and potential biases.
Additional Notes 
Model not aligned with RLHF, may produce unaligned outputs.
Supported Languages 
English (primary), programming_languages (600+)
Training Details 
Data Sources:
HuggingFaceH4/ultrafeedback_binarized, HuggingFaceH4/orca_dpo_pairs
Methodology:
Fine-tuned from StarCoder2, using SFT and DPO techniques.
Hardware Used:
multi-GPU, 8 devices
Model Architecture:
GPT-like
Input Output 
Input Format:
Messages in chat format
Accepted Modalities:
text
Output Format:
Generated text responses
Performance Tips:
Utilize pipelines for optimal performance.
LLM NameStarchat2 15B V0.1 AWQ
Repository 🤗https://huggingface.co/stelterlab/starchat2-15b-v0.1-AWQ 
Base Model(s)  HuggingFaceH4/starchat2-15b-sft-v0.1   HuggingFaceH4/starchat2-15b-sft-v0.1
Model Size15b
Required VRAM9.2 GB
Updated2026-04-28
Maintainerstelterlab
Model Typestarcoder2
Model Files  9.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureStarcoder2ForCausalLM
Licensebigcode-openrail-m
Context Length16384
Model Max Length16384
Transformers Version4.40.1
Tokenizer ClassGPT2Tokenizer
Padding Token<|im_end|>
Vocabulary Size49154
Torch Data Typefloat16

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...rCoder2 15B Instruct V0.1 GGUF16K / 6.2 GB940
...rCoder2 15B Instruct V0.1 GGUF16K / 6.2 GB610
Note: green Score (e.g. "73.2") means that the model is better than stelterlab/starchat2-15b-v0.1-AWQ.

Rank the Starchat2 15B V0.1 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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