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Starling LM 7B Alpha GPTQ by TheBloke

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  Arxiv:2306.02231   4-bit   Autotrain compatible Base model:berkeley-nest/starl... Base model:quantized:berkeley-...   Conversational   Dataset:berkeley-nest/nectar   En   Gptq   Mistral   Quantized   Region:us   Reward model   Rlaif   Rlhf   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/Starling-LM-7B-alpha-GPTQ 

Starling LM 7B Alpha GPTQ Benchmarks

LLME Score: 0.14807
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Starling LM 7B Alpha GPTQ (TheBloke/Starling-LM-7B-alpha-GPTQ)

Starling LM 7B Alpha GPTQ Parameters and Internals

Model Type 
Language Model, Mistral
Use Cases 
Areas:
Research
Additional Notes 
The model uses the same chat template as Openchat 3.5.
Supported Languages 
en (efficient)
Training Details 
Data Sources:
berkeley-nest/Nectar
Methodology:
Advantage-Induced Policy Alignment (APA)
Input Output 
Input Format:
Prompt template: OpenChat
Accepted Modalities:
text
Output Format:
Text generation
LLM NameStarling LM 7B Alpha GPTQ
Repository 🤗https://huggingface.co/TheBloke/Starling-LM-7B-alpha-GPTQ 
Model NameStarling LM 7B Alpha
Model CreatorBerkeley-Nest
Base Model(s)  Starling LM 7B Alpha   berkeley-nest/Starling-LM-7B-alpha
Model Size7b
Required VRAM4.2 GB
Updated2025-02-23
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMistralForCausalLM
Licensecc-by-nc-4.0
Context Length8192
Model Max Length8192
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token<|end_of_turn|>
Vocabulary Size32002
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Starling-LM-7B-alpha-GPTQ.

Rank the Starling LM 7B Alpha GPTQ 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 v20241227
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