What are the hardware requirements for Llama 3.1 8B Reponx Network Cloud Ops?

Llama 3.1 8B Reponx Network Cloud Ops requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 3.1 8B Reponx Network Cloud Ops and how large is it?

Llama 3.1 8B Reponx Network Cloud Ops is developed by Reponx, a model with 8b 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 3.1 8B Reponx Network Cloud Ops?

Llama 3.1 8B Reponx Network Cloud Ops is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3.1 8B Reponx Network Cloud Ops by Reponx — VRAM 0.2GB

Name: Llama 3.1 8B Reponx Network Cloud Ops
Author: Reponx

Llama 3.1 8B Reponx Network Cloud Ops is an open-source language model by Reponx. Features: 8b LLM, VRAM: 0.2GB, License: llama3.1, Instruction-Based, LLM Explorer Score: 0.28.

Adapter Aws Azure Base model:adapter:meta-llama/... Base model:meta-llama/llama-3.... Bgp Cisco Cloud-operations Conversational Dataset:reponx/network-cloud-o... En Finetuned Instruct Lora Network-engineering Network-operations Network-troubleshooting Ospf Palo-alto-networks Peft Rag Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Reponx/Llama-3.1-8B-Reponx-Network-Cloud-Ops

Llama 3.1 8B Reponx Network Cloud Ops Parameters and Internals

LLM Name	Llama 3.1 8B Reponx Network Cloud Ops
Repository 🤗	https://huggingface.co/Reponx/Llama-3.1-8B-Reponx-Network-Cloud-Ops
Base Model(s)	meta-llama/Llama-3.1-8B-Instruct meta-llama/Llama-3.1-8B-Instruct
Model Size	8b
Required VRAM	0.2 GB
Updated	2026-10-12
Maintainer	Reponx
Instruction-Based	Yes
Model Files	0.2 GB
Supported Languages	en
Model Architecture	Adapter
License	llama3.1
Model Max Length	131072
Is Biased	none
Tokenizer Class	TokenizersBackend
Padding Token	<\|eot_id\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	k_proj\|gate_proj\|v_proj\|up_proj\|down_proj\|o_proj\|q_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16

Rank the Llama 3.1 8B Reponx Network Cloud Ops capabilities

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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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