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Mistral 7B Instruct V0.2 GGUF by alokabhishek

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Mistral 7B Instruct V0.2 GGUF is an open-source language model by alokabhishek. Features: 7b LLM, VRAM: 4.4GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, HF Score: 65.7, LLM Explorer Score: 0.24, ELO: 1072, Arc: 63.1, HellaSwag: 84.9, MMLU: 60.8, TruthfulQA: 68.3, WinoGrande: 77.2, GSM8K: 40.

  4bit   Autotrain compatible   Conversational   Endpoints compatible   Gguf   Instruct   Mistral   Mistral-7b   Pytorch   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/alokabhishek/Mistral-7B-Instruct-v0.2-GGUF 

Mistral 7B Instruct V0.2 GGUF Benchmarks

LMSys ELO: 1072 vs 1272 (so35)-15.7%
ARC: 63.14 vs 96.7 (so35)-34.7%
HellaSwag: 84.88 vs 95.3 (gpt4)-10.9%
MMLU: 60.78 vs 88.3 (so35)-31.2%
TruthfulQA: 68.26 vs 59 (gpt4)15.7%
WinoGrande: 77.19 vs 87.5 (gpt4)-11.8%
GSM8K: 40.03 vs 96.4 (so35)-58.5%
LLME Score: 0.24343
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 V0.2 GGUF (alokabhishek/Mistral-7B-Instruct-v0.2-GGUF)
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Mistral 7B Instruct V0.2 GGUF Parameters and Internals

Model Type 
text generation
Use Cases 
Applications:
text-generation
LLM NameMistral 7B Instruct V0.2 GGUF
Repository 🤗https://huggingface.co/alokabhishek/Mistral-7B-Instruct-v0.2-GGUF 
Base Model(s)  malhajar/Mistral-7B-Instruct-v0.2-turkish   malhajar/Mistral-7B-Instruct-v0.2-turkish
Model Size7b
Required VRAM4.4 GB
Updated2025-09-23
Maintaineralokabhishek
Model Typemistral
Instruction-BasedYes
Model Files  4.4 GB   5.1 GB
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than alokabhishek/Mistral-7B-Instruct-v0.2-GGUF.

Rank the Mistral 7B Instruct V0.2 GGUF 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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