What are the hardware requirements for Mika 7B LoRA?

Mika 7B LoRA requires approximately 15 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mika 7B LoRA and how large is it?

Mika 7B LoRA is developed by Epiculous, 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 Mika 7B LoRA?

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

Mika 7B LoRA by Epiculous — VRAM 15GB

Name: Mika 7B LoRA
Author: Epiculous

Mika 7B LoRA is an open-source language model by Epiculous. Features: 7b LLM, VRAM: 15GB, LLM Explorer Score: 0.11.

Arxiv:1910.09700 8-bit Adapter Base model:adapter:mistralai/m... Base model:mistralai/mistral-7... Bitsandbytes Dataset:chaoticneutrals/synthe... Dataset:chaoticneutrals/synthe... Dataset:epiculous/gnosis Dataset:grimulkan/theory-of-mi... Dataset:lemonilia/limarp Finetuned Lora Mistral Peft Pytorch Region:us Safetensors Sharded

Model Card on HF 🤗: https://huggingface.co/Epiculous/Mika-7B-LoRA

Mika 7B LoRA Parameters and Internals

LLM Name	Mika 7B LoRA
Repository 🤗	https://huggingface.co/Epiculous/Mika-7B-LoRA
Base Model(s)	mistralai/Mistral-7B-v0.1 mistralai/Mistral-7B-v0.1
Model Size	7b
Required VRAM	15 GB
Updated	2026-06-03
Maintainer	Epiculous
Model Files	0.3 GB 0.3 GB 0.7 GB 5.0 GB: 1-of-4 4.9 GB: 2-of-4 4.6 GB: 3-of-4 0.5 GB: 4-of-4 0.0 GB 0.0 GB
Model Architecture	Adapter
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	up_proj\|q_proj\|down_proj\|v_proj\|gate_proj\|k_proj\|o_proj
LoRA Alpha	16
LoRA Dropout	0.05
R Param	32

Rank the Mika 7B LoRA 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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Zduhac Cyber 7B V2	0K / 0 GB	8	1
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Mistral 7B Instruct Vi Alpaca	0K / 0.4 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than Epiculous/Mika-7B-LoRA.