What are the hardware requirements for Vigogne 2 7B Instruct GPTQ?

Vigogne 2 7B Instruct GPTQ requires approximately 3.9 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Vigogne 2 7B Instruct GPTQ and how large is it?

Vigogne 2 7B Instruct GPTQ is developed by TheBloke, 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 Vigogne 2 7B Instruct GPTQ?

Vigogne 2 7B Instruct GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Vigogne 2 7B Instruct GPTQ by TheBloke — VRAM 3.9GB, 2K context

Name: Vigogne 2 7B Instruct GPTQ
Author: TheBloke

Vigogne 2 7B Instruct GPTQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 3.9GB, Context: 2K, License: llama2, Quantized, Instruction-Based, LLM Explorer Score: 0.08.

4-bit Base model:bofenghuang/vigogne... Base model:quantized:bofenghua... Fr Gptq Instruct Llama Llama2 Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Vigogne-2-7B-Instruct-GPTQ

Vigogne 2 7B Instruct GPTQ Parameters and Internals

Model Type

text-generation

Input Output

Input Format:

Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {prompt} ### Response:

Accepted Modalities:

text

Output Format:

Text

LLM Name	Vigogne 2 7B Instruct GPTQ
Repository 🤗	https://huggingface.co/TheBloke/Vigogne-2-7B-Instruct-GPTQ
Model Name	Vigogne 2 7B Instruct
Model Creator	bofenghuang
Base Model(s)	Vigogne 2 7B Instruct bofenghuang/vigogne-2-7b-instruct
Model Size	7b
Required VRAM	3.9 GB
Updated	2026-06-28
Maintainer	TheBloke
Model Type	llama
Instruction-Based	Yes
Model Files	3.9 GB
Supported Languages	fr
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	2048
Model Max Length	2048
Transformers Version	4.32.0.dev0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Vigogne 2 7B Instruct GPTQ 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 Vigogne 2 7B Instruct GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
... 7B 32K Instructions V4 Marlin	32K / 4.1 GB	8	0
Llama 2 7B 32K Instruct GPTQ	32K / 3.9 GB	49	27
...a 7B Instruct GPTQ Calib Ja 1K	16K / 3.9 GB	6	0
...echless Tora Code 7B V1.0 GPTQ	16K / 3.9 GB	9	1
CodeLlama 7B Instruct GPTQ	16K / 3.9 GB	499	46
CausalLM 7B GPTQ	8K / 5.9 GB	7	5
Leo Hessianai 7B Chat GPTQ	8K / 3.9 GB	18	0
...ssianai 7B Chat Bilingual GPTQ	8K / 3.9 GB	6	0
Xgen 7B 8K Open Instruct Gptq	8K / 4.2 GB	5	4
Deepseek Math 7B Instruct GPTQ	4K / 4.8 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Vigogne-2-7B-Instruct-GPTQ.