What are the hardware requirements for Mistral 7B V0.1 AviationQA?

Mistral 7B V0.1 AviationQA requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistral 7B V0.1 AviationQA and how large is it?

Mistral 7B V0.1 AviationQA is developed by frankmorales2020, 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 Mistral 7B V0.1 AviationQA?

Mistral 7B V0.1 AviationQA is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral 7B V0.1 AviationQA by frankmorales2020 — VRAM 0.1GB

Name: Mistral 7B V0.1 AviationQA
Author: frankmorales2020

Mistral 7B V0.1 AviationQA is an open-source language model by frankmorales2020. Features: 7b LLM, VRAM: 0.1GB, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.12.

Adapter Base model:adapter:mistralai/m... Base model:mistralai/mistral-7... Finetuned Generated from trainer Instruct Lora Peft Region:us Safetensors Tensorboard

Model Card on HF 🤗: https://huggingface.co/frankmorales2020/Mistral-7B-v0.1_AviationQA

Mistral 7B V0.1 AviationQA Parameters and Internals

Training Details

Data Sources:

generator

LLM Name	Mistral 7B V0.1 AviationQA
Repository 🤗	https://huggingface.co/frankmorales2020/Mistral-7B-v0.1_AviationQA
Base Model(s)	mistralai/Mistral-7B-Instruct-v0.1 mistralai/Mistral-7B-Instruct-v0.1
Model Size	7b
Required VRAM	0.1 GB
Updated	2026-07-21
Maintainer	frankmorales2020
Instruction-Based	Yes
Model Files	0.1 GB 0.0 GB
Model Architecture	Adapter
License	apache-2.0
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	down_proj\|up_proj\|gate_proj\|k_proj\|v_proj\|q_proj\|o_proj
LoRA Alpha	32
LoRA Dropout	0.1
R Param	8

Rank the Mistral 7B V0.1 AviationQA 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 frankmorales2020/Mistral-7B-v0.1_AviationQA.