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VolareQuantized by MoxoffSpA

 »  All LLMs  »  MoxoffSpA  »  VolareQuantized   URL Share it on

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

VolareQuantized Benchmarks

LLME Score: 0.15415
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
VolareQuantized (MoxoffSpA/VolareQuantized)
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VolareQuantized Parameters and Internals

Model Type 
chatml, sft, it
Additional Notes 
The model is offered in 4-bit and 8-bit configurations, designed for efficiency.
Supported Languages 
it (high), en (high)
Training Details 
Data Sources:
https://huggingface.co/datasets/squad_it
Context Length:
2048
Input Output 
Input Format:
[INST] {prompt} [/INST]
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Set n_gpu_layers to number of layers to offload to GPU, set to 0 if no GPU is available.
LLM NameVolareQuantized
Repository 🤗https://huggingface.co/MoxoffSpA/VolareQuantized 
Model Size7b
Required VRAM5.3 GB
Updated2025-01-13
MaintainerMoxoffSpA
Model Typegemma
Model Files  5.3 GB   9.1 GB
Supported Languagesit en
GGML QuantizationYes
GGUF QuantizationYes
Quantization Typegguf|ggml|q4|q4_k
Model ArchitectureGemmaForCausalLM
Licensemit
Context Length8192
Model Max Length8192
Transformers Version4.38.0
Vocabulary Size256000
Torch Data Typefloat16

Best Alternatives to VolareQuantized

Best Alternatives
Context / RAM
Downloads
Likes
CNCF8K / 5.3 GB510
Gemma 7B Uawiki 1B8K / 17.1 GB240
DeepCNCFQuantized8K / 5.3 GB121
VolareQuantized8K / 5.3 GB181
Gemma 7B It8K / 17.1 GB2085241210
Gemma 7B8K / 17.1 GB452553203
Gemma 1.1 7B It GGUF8K / 5.3 GB751
Train068K / 9.1 GB500
Llama2 Kazakh 7B GGUF8K / 4.1 GB150
Gemma 7B It GGUF8K / 3.1 GB147611
Note: green Score (e.g. "73.2") means that the model is better than MoxoffSpA/VolareQuantized.

Rank the VolareQuantized 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 v20241124
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