What are the hardware requirements for LlamaGuard 7B GPTQ 4bit 128g Actorder True?

LlamaGuard 7B GPTQ 4bit 128g Actorder True requires approximately 2.9 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 LlamaGuard 7B GPTQ 4bit 128g Actorder True and how large is it?

LlamaGuard 7B GPTQ 4bit 128g Actorder True is developed by SebastianSchramm, 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 LlamaGuard 7B GPTQ 4bit 128g Actorder True?

LlamaGuard 7B GPTQ 4bit 128g Actorder True is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

LlamaGuard 7B GPTQ 4bit 128g Actorder True by SebastianSchramm — VRAM 2.9GB, 2K context

Name: LlamaGuard 7B GPTQ 4bit 128g Actorder True
Author: SebastianSchramm

LlamaGuard 7B GPTQ 4bit 128g Actorder True is an open-source language model by SebastianSchramm. Features: 7b LLM, VRAM: 2.9GB, Context: 2K, License: llama2, Quantized, LLM Explorer Score: 0.1.

4-bit 4bit Base model:meta-llama/llamagua... Base model:quantized:meta-llam... Conversational En Facebook Gptq Llama Llama2 Meta Pytorch Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/SebastianSchramm/LlamaGuard-7b-GPTQ-4bit-128g-actorder_True

LlamaGuard 7B GPTQ 4bit 128g Actorder True Parameters and Internals

Model Type

quantized

Additional Notes

Refer to quantization details outlined.

Supported Languages

en (high)

Training Details

Methodology:

quantized to 4bit, group_size 128, act-order=True with auto-gptq integration

LLM Name	LlamaGuard 7B GPTQ 4bit 128g Actorder True
Repository 🤗	https://huggingface.co/SebastianSchramm/LlamaGuard-7b-GPTQ-4bit-128g-actorder_True
Base Model(s)	LlamaGuard 7B meta-llama/LlamaGuard-7b
Model Size	7b
Required VRAM	2.9 GB
Updated	2026-08-08
Maintainer	SebastianSchramm
Model Type	llama
Model Files	1.0 GB: 2-of-4 1.0 GB: 3-of-4 0.9 GB: 4-of-4
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq\|4bit
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	2048
Model Max Length	2048
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the LlamaGuard 7B GPTQ 4bit 128g Actorder True capabilities

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Instruction Following and Task Automation
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Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
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Code Generation
Multi-Language Support and Translation

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Note: green Score (e.g. "73.2") means that the model is better than SebastianSchramm/LlamaGuard-7b-GPTQ-4bit-128g-actorder_True.