What are the hardware requirements for Llama 2 13B Chat Hf GPT 4 80K?

Llama 2 13B Chat Hf GPT 4 80K requires approximately 26 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 2 13B Chat Hf GPT 4 80K and how large is it?

Llama 2 13B Chat Hf GPT 4 80K is developed by JunchengXie, a model with 13b 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 2 13B Chat Hf GPT 4 80K?

Llama 2 13B Chat Hf GPT 4 80K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 2 13B Chat Hf GPT 4 80K by JunchengXie — VRAM 26GB

Name: Llama 2 13B Chat Hf GPT 4 80K
Author: JunchengXie

Llama 2 13B Chat Hf GPT 4 80K is an open-source language model by JunchengXie. Features: 13b LLM, VRAM: 26GB, License: apache-2.0, LLM Explorer Score: 0.12.

Conversational Endpoints compatible Llama Lora Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/JunchengXie/Llama-2-13b-chat-hf-gpt-4-80k

Llama 2 13B Chat Hf GPT 4 80K Parameters and Internals

Additional Notes

This model is finetuned on the distillation data from GPT-4.

Input Output

Input Format:

~~[INST] <> {query} [/INST]

LLM Name	Llama 2 13B Chat Hf GPT 4 80K
Repository 🤗	https://huggingface.co/JunchengXie/Llama-2-13b-chat-hf-gpt-4-80k
Model Size	13b
Required VRAM	26 GB
Updated	2026-07-25
Maintainer	JunchengXie
Model Files	0.1 GB 5.0 GB: 1-of-6 5.0 GB: 2-of-6 5.0 GB: 3-of-6 4.9 GB: 4-of-6 4.9 GB: 5-of-6 1.2 GB: 6-of-6
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Is Biased	none
Tokenizer Class	LlamaTokenizer
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	k_proj\|o_proj\|v_proj\|down_proj\|gate_proj\|q_proj\|up_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	8

Rank the Llama 2 13B Chat Hf GPT 4 80K 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

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Note: green Score (e.g. "73.2") means that the model is better than JunchengXie/Llama-2-13b-chat-hf-gpt-4-80k.