What are the hardware requirements for Mistral 7B V0.3 Finetuned?

Mistral 7B V0.3 Finetuned requires approximately 14.5 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistral 7B V0.3 Finetuned and how large is it?

Mistral 7B V0.3 Finetuned is developed by formalmathatepfl, 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 V0.3 Finetuned?

Mistral 7B V0.3 Finetuned is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral 7B V0.3 Finetuned by formalmathatepfl — VRAM 14.5GB, 32K context

Name: Mistral 7B V0.3 Finetuned
Author: formalmathatepfl

Mistral 7B V0.3 Finetuned is an open-source language model by formalmathatepfl. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: other, Fine-Tuned, LLM Explorer Score: 0.23.

Base model:finetune:mistralai/... Base model:mistralai/mistral-7... Conversational Endpoints compatible Finetuned Full Generated from trainer Llama-factory Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/formalmathatepfl/mistral-7B-v0.3-finetuned

Mistral 7B V0.3 Finetuned Parameters and Internals

LLM Name	Mistral 7B V0.3 Finetuned
Repository 🤗	https://huggingface.co/formalmathatepfl/mistral-7B-v0.3-finetuned
Base Model(s)	mistralai/Mistral-7B-v0.3 mistralai/Mistral-7B-v0.3
Model Size	7b
Required VRAM	14.5 GB
Updated	2026-08-01
Maintainer	formalmathatepfl
Model Type	mistral
Model Files	5.0 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3 0.0 GB
Model Architecture	MistralForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.57.3
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32768

Rank the Mistral 7B V0.3 Finetuned 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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