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MistralLite AWQ by amazon

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MistralLite AWQ is an open-source language model by amazon. Features: 7.2b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.13.

  Arxiv:2306.00978   4-bit   Awq   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/amazon/MistralLite-AWQ 

MistralLite AWQ Benchmarks

LLME Score: 0.1336
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MistralLite AWQ (amazon/MistralLite-AWQ)
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MistralLite AWQ Parameters and Internals

Model Type 
Quantized Model
LLM NameMistralLite AWQ
Repository 🤗https://huggingface.co/amazon/MistralLite-AWQ 
Model Size7.2b
Required VRAM4.2 GB
Updated2026-05-04
Maintaineramazon
Model Typemistral
Model Files  4.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.40.2
Tokenizer ClassLlamaTokenizer
Padding Token[PAD]
Vocabulary Size32003
Torch Data Typefloat16

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Functionary Small V2.4 AWQ32K / 4.2 GB91
Hc Mistral Alpaca Merged AWQ32K / 4.2 GB90
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HamSter 0.1 AWQ32K / 4.2 GB42
Phoenix AWQ32K / 4.2 GB61
...ph Openchat 3.5 1210 Slerp AWQ32K / 4.2 GB82
Mistral Ft Optimized 1227 AWQ32K / 4.2 GB81
Note: green Score (e.g. "73.2") means that the model is better than amazon/MistralLite-AWQ.

Rank the MistralLite AWQ 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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