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Mistral Ft Optimized 1227 AWQ by TheBloke

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Mistral Ft Optimized 1227 AWQ is an open-source language model by TheBloke. Features: 7.2b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.11.

  4-bit   Awq Base model:openpipe/mistral-ft... Base model:quantized:openpipe/...   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/mistral-ft-optimized-1227-AWQ 

Mistral Ft Optimized 1227 AWQ Benchmarks

LLME Score: 0.10825
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral Ft Optimized 1227 AWQ (TheBloke/mistral-ft-optimized-1227-AWQ)
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Mistral Ft Optimized 1227 AWQ Parameters and Internals

Model Type 
mistral
Additional Notes 
The model is an AWQ quantized version, offering efficient low-bit weight quantization for better inference speed while maintaining accuracy.
LLM NameMistral Ft Optimized 1227 AWQ
Repository 🤗https://huggingface.co/TheBloke/mistral-ft-optimized-1227-AWQ 
Model NameMistral FT Optimized 1227
Model CreatorOpenPipe
Base Model(s)  Mistral Ft Optimized 1227   OpenPipe/mistral-ft-optimized-1227
Model Size7.2b
Required VRAM4.2 GB
Updated2026-05-21
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
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/mistral-ft-optimized-1227-AWQ.

Rank the Mistral Ft Optimized 1227 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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