What are the hardware requirements for Mistral Wikitable FV?

Mistral Wikitable FV requires approximately 0.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistral Wikitable FV and how large is it?

Mistral Wikitable FV is developed by moetezsa, 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 Wikitable FV?

Mistral Wikitable FV is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral Wikitable FV by moetezsa — VRAM 0.3GB

Name: Mistral Wikitable FV
Author: moetezsa

Mistral Wikitable FV is an open-source language model by moetezsa. Features: 7b LLM, VRAM: 0.3GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

4bit Adapter Base model:adapter:unsloth/mis... Base model:unsloth/mistral-7b-... Finetuned Generated from trainer Instruct Lora Peft Quantized Region:us Safetensors Sft Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/moetezsa/mistral_wikitable_FV

Mistral Wikitable FV Parameters and Internals

Model Type

trl, sft, unsloth, generated_from_trainer

Additional Notes

This model provides insights into its training procedure including hyperparameters and performance metrics through epochs.

LLM Name	Mistral Wikitable FV
Repository 🤗	https://huggingface.co/moetezsa/mistral_wikitable_FV
Base Model(s)	unsloth/mistral-7b-instruct-v0.2-bnb-4bit unsloth/mistral-7b-instruct-v0.2-bnb-4bit
Model Size	7b
Required VRAM	0.3 GB
Updated	2026-04-24
Maintainer	moetezsa
Instruction-Based	Yes
Model Files	0.3 GB 0.0 GB
Quantization Type	4bit
Model Architecture	Adapter
License	apache-2.0
Model Max Length	32768
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	v_proj\|k_proj\|down_proj\|up_proj\|o_proj\|gate_proj\|q_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	32

Rank the Mistral Wikitable FV 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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Falcon 7B Instruct 4bit Lora	0K / 0 GB	0	1
Fedquant Mistral 7B Lora	0K / 0 GB	22	1
Lemonilia ShoriRP V0.75d	0K / 0.2 GB	8	1
Falcon3 7B Persian Lora	0K / 0.2 GB	22	2

Note: green Score (e.g. "73.2") means that the model is better than moetezsa/mistral_wikitable_FV.