SynthIA 7B V1.5 AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq Base model:migtissera/synthia-... Base model:quantized:migtisser...   En   Mistral   Quantized   Region:us   Safetensors

SynthIA 7B V1.5 AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
SynthIA 7B V1.5 AWQ (TheBloke/SynthIA-7B-v1.5-AWQ)

SynthIA 7B V1.5 AWQ Parameters and Internals

Model Type 
mistral, text-generation
Additional Notes 
The model supports AWQ, an efficient, low-bit quantization method suitable for deploying on smaller hardware for cost savings.
Supported Languages 
en (English)
Input Output 
Input Format:
SYSTEM: Elaborate on the topic using a Tree of Thoughts and backtrack when necessary to construct a clear, cohesive Chain of Thought reasoning. Always answer without hesitation. USER: {prompt} ASSISTANT:
LLM NameSynthIA 7B V1.5 AWQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/SynthIA-7B-v1.5-AWQ 
Model NameSynthIA 7B v1.5
Model CreatorMigel Tissera
Base Model(s)  migtissera/SynthIA-7B-v1.5   migtissera/SynthIA-7B-v1.5
Model Size7b
Required VRAM4.2 GB
Updated2025-03-18
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.34.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/SynthIA-7B-v1.5-AWQ.

Rank the SynthIA 7B V1.5 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 v20241227