What are the hardware requirements for VolareQuantized?

VolareQuantized requires approximately 5.3 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed VolareQuantized and how large is it?

VolareQuantized is developed by MoxoffSpA, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate VolareQuantized?

VolareQuantized is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

VolareQuantized by MoxoffSpA — VRAM 5.3GB, 8K context

Name: VolareQuantized
Author: MoxoffSpA

VolareQuantized is an open-source language model by MoxoffSpA. Features: 7b LLM, VRAM: 5.3GB, Context: 8K, License: mit, Quantized, LLM Explorer Score: 0.12.

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 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 Name	VolareQuantized
Repository 🤗	https://huggingface.co/MoxoffSpA/VolareQuantized
Model Size	7b
Required VRAM	5.3 GB
Updated	2025-01-13
Maintainer	MoxoffSpA
Model Type	gemma
Model Files	5.3 GB 9.1 GB
Supported Languages	it en
GGML Quantization	Yes
GGUF Quantization	Yes
Quantization Type	gguf\|ggml\|q4\|q4_k
Model Architecture	GemmaForCausalLM
License	mit
Context Length	8192
Model Max Length	8192
Transformers Version	4.38.0
Vocabulary Size	256000
Torch Data Type	float16

Rank the VolareQuantized capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to VolareQuantized

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 7B Uawiki 1B	8K / 17.1 GB	24	0
CNCF	8K / 5.3 GB	25	0
DeepCNCFQuantized	8K / 5.3 GB	17	1
VolareQuantized	8K / 5.3 GB	144	1
Gemma 7B It	8K / 17.1 GB	24944	1250
Gemma 7B	8K / 17.1 GB	29051	3388
Gemma 1.1 7B It GGUF	8K / 5.3 GB	52	1
Train06	8K / 9.1 GB	22	0
Llama2 Kazakh 7B GGUF	8K / 4.1 GB	10	0
Gemma 7B	8K / 17.1 GB	39	0

Note: green Score (e.g. "73.2") means that the model is better than MoxoffSpA/VolareQuantized.