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AzzurroQuantized by MoxoffSpA

 »  All LLMs  »  MoxoffSpA  »  AzzurroQuantized   URL Share it on

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  Autotrain compatible   Chatml   Conversational   En   Endpoints compatible   Ggml   Gguf   It   Mistral   Q4   Quantized   Region:us   Sft
Model Card on HF 🤗: https://huggingface.co/MoxoffSpA/AzzurroQuantized 

AzzurroQuantized Benchmarks

LLME Score: 0.18583
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
AzzurroQuantized (MoxoffSpA/AzzurroQuantized)

AzzurroQuantized Parameters and Internals

Model Type 
text generation
Use Cases 
Primary Use Cases:
Retrieval Augmented Generation (RAG) tasks and applications requiring contextual awareness
Limitations:
Not aligned to human preferences for safety, Can produce problematic outputs
Supported Languages 
Italian (Highly Proficient), English (Highly Proficient)
Training Details 
Data Sources:
publicly available datasets, created in-house datasets
Context Length:
2048
Input Output 
Accepted Modalities:
text
Output Format:
text
LLM NameAzzurroQuantized
Repository 🤗https://huggingface.co/MoxoffSpA/AzzurroQuantized 
Model Size7b
Required VRAM4.4 GB
Updated2025-01-13
MaintainerMoxoffSpA
Model Typemistral
Model Files  4.4 GB   7.7 GB
Supported Languagesit en
GGML QuantizationYes
GGUF QuantizationYes
Quantization Typegguf|ggml|q4|q4_k
Model ArchitectureMistralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.38.0
Vocabulary Size32000
Torch Data Typefloat32

Best Alternatives to AzzurroQuantized

Best Alternatives
Context / RAM
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Likes
Mistrilitary 7B32K / 7.7 GB12819
Mistral Scary Story Finetune32K / 14.5 GB300
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Instruct 16bit32K / 0.4 GB50
Merlinite 7B Ocp4.15 V0.332K / 14.5 GB90
Shiftdocs 7B Ocp4.15 V0.332K / 14.5 GB110
AzzurroQuantized32K / 4.4 GB2224
Merlinite 7B Ocp4.15 V0.132K / 4.4 GB120
Filiberto 7B Instruct Exp132K / 14.5 GB310
MistralMusic32K / 14.4 GB261
Note: green Score (e.g. "73.2") means that the model is better than MoxoffSpA/AzzurroQuantized.

Rank the AzzurroQuantized 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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