What are the hardware requirements for Llama Tagger HF GPTQ 4bits?

Llama Tagger HF GPTQ 4bits 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 Llama Tagger HF GPTQ 4bits and how large is it?

Llama Tagger HF GPTQ 4bits is developed by John6666, a model with 6.7b 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 Llama Tagger HF GPTQ 4bits?

Llama Tagger HF GPTQ 4bits is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama Tagger HF GPTQ 4bits by John6666 — VRAM 3.9GB, 2K context

Name: Llama Tagger HF GPTQ 4bits
Author: John6666

Llama Tagger HF GPTQ 4bits is an open-source language model by John6666. Features: 6.7b LLM, VRAM: 3.9GB, Context: 2K, License: mit, Quantized, LLM Explorer Score: 0.13.

4-bit Gptq Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/John6666/llama-tagger-HF-GPTQ-4bits

Llama Tagger HF GPTQ 4bits Parameters and Internals

LLM Name	Llama Tagger HF GPTQ 4bits
Repository 🤗	https://huggingface.co/John6666/llama-tagger-HF-GPTQ-4bits
Model Size	6.7b
Required VRAM	3.9 GB
Updated	2026-07-21
Maintainer	John6666
Model Type	llama
Model Files	3.9 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	LlamaForCausalLM
License	mit
Context Length	2048
Model Max Length	2048
Transformers Version	4.42.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

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