What are the hardware requirements for Mistral 7B Base Sft?

Mistral 7B Base Sft 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 Base Sft and how large is it?

Mistral 7B Base Sft is developed by NLP-Final-Project, 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 Base Sft?

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

Mistral 7B Base Sft by NLP-Final-Project — VRAM 14.5GB, 32K context

Name: Mistral 7B Base Sft
Author: NLP-Final-Project

Mistral 7B Base Sft is an open-source language model by NLP-Final-Project. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, LLM Explorer Score: 0.23.

Base model:finetune:mistralai/... Base model:mistralai/mistral-7... Endpoints compatible Generated from trainer Mistral Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/NLP-Final-Project/mistral-7b-base-sft

Mistral 7B Base Sft Parameters and Internals

LLM Name	Mistral 7B Base Sft
Repository 🤗	https://huggingface.co/NLP-Final-Project/mistral-7b-base-sft
Model Name	mistral-7b-base-sft
Base Model(s)	mistralai/Mistral-7B-v0.1 mistralai/Mistral-7B-v0.1
Model Size	7b
Required VRAM	14.5 GB
Updated	2026-05-31
Maintainer	NLP-Final-Project
Model Type	mistral
Model Files	14.5 GB 0.0 GB
Model Architecture	MistralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	5.8.0
Tokenizer Class	TokenizersBackend
Padding Token	</s>
Vocabulary Size	32000

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