What are the hardware requirements for Nyan Stunna 7B?

Nyan Stunna 7B requires approximately 14.4 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 Nyan Stunna 7B and how large is it?

Nyan Stunna 7B is developed by Nitral-AI, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Nyan Stunna 7B perform on standard benchmarks?

Nyan Stunna 7B has the following published scores: MMLU 64.58. Compare against reference models on this page or on the LLM Explorer leaderboards.

Nyan Stunna 7B by Nitral-AI — VRAM 14.4GB, 32K context

Name: Nyan Stunna 7B
Author: Nitral-AI

Nyan Stunna 7B is an open-source language model by Nitral-AI. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: other, Merged, LLM Explorer Score: 0.13, Arc: 66.4, HellaSwag: 85.6, MMLU: 64.6, GSM8K: 55.7.

Merged Model Autotrain compatible Base model:arlineka/kittynyans... Base model:nitral-ai/kukulstan... Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Nitral-AI/Nyan-Stunna-7B

Nyan Stunna 7B Parameters and Internals

Model Type

multimodal

Additional Notes

Vision functionality requires loading a specific mmproj file.

Input Output

Accepted Modalities:

vision

LLM Name	Nyan Stunna 7B
Repository 🤗	https://huggingface.co/Nitral-AI/Nyan-Stunna-7B
Base Model(s)	KittyNyanster V1 KukulStanta 7B arlineka/KittyNyanster-v1 Nitral-AI/KukulStanta-7B
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2025-02-03
Maintainer	Nitral-AI
Model Type	mistral
Model Files	2.0 GB: 1-of-8 1.9 GB: 2-of-8 2.0 GB: 3-of-8 1.9 GB: 4-of-8 1.9 GB: 5-of-8 1.9 GB: 6-of-8 1.9 GB: 7-of-8 0.9 GB: 8-of-8
Model Architecture	MistralForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Nyan Stunna 7B 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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...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than Nitral-AI/Nyan-Stunna-7B.