Mistral 7B Instruct V0.3 AWQ by solidrust

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  4-bit   Autotrain compatible   Awq Base model:mistralai/mistral-7... Base model:quantized:mistralai...   Conversational   Endpoints compatible   Instruct   Mistral   Quantized   Region:us   Safetensors

Mistral 7B Instruct V0.3 AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral 7B Instruct V0.3 AWQ (solidrust/Mistral-7B-Instruct-v0.3-AWQ)

Mistral 7B Instruct V0.3 AWQ Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
research, commercial applications
Additional Notes 
The model supports function calling and utilizes a v3 tokenizer.
Training Details 
Methodology:
Instruct fine-tuning
Input Output 
Accepted Modalities:
text
Performance Tips:
Utilize AWQ supported platforms for optimal performance.
LLM NameMistral 7B Instruct V0.3 AWQ
Repository ๐Ÿค—https://huggingface.co/solidrust/Mistral-7B-Instruct-v0.3-AWQ 
Base Model(s)  mistralai/Mistral-7B-Instruct-v0.3   mistralai/Mistral-7B-Instruct-v0.3
Model Size7b
Required VRAM4.2 GB
Updated2024-12-21
Maintainersolidrust
Model Typemistral
Instruction-BasedYes
Model Files  4.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.41.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32768
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than solidrust/Mistral-7B-Instruct-v0.3-AWQ.

Rank the Mistral 7B Instruct V0.3 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217