What are the hardware requirements for Oumuamua 7B Instruct V2 RP?

Oumuamua 7B Instruct V2 RP requires approximately 14.6 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 Oumuamua 7B Instruct V2 RP and how large is it?

Oumuamua 7B Instruct V2 RP is developed by Aratako, 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 Oumuamua 7B Instruct V2 RP?

Oumuamua 7B Instruct V2 RP is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Oumuamua 7B Instruct V2 RP by Aratako — VRAM 14.6GB, 32K context

Name: Oumuamua 7B Instruct V2 RP
Author: Aratako

Oumuamua 7B Instruct V2 RP is an open-source language model by Aratako. Features: 7b LLM, VRAM: 14.6GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.13.

Conversational Dataset:aratako/bluemoon top50... Dataset:aratako/limarp-augment... Dataset:aratako/rosebleu-1on1-... Dataset:grimulkan/limarp-augme... Dataset:omniaicreator/japanese... Dataset:omniaicreator/japanese... Dataset:sicariussicariistuff/b... Endpoints compatible Instruct Ja Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Aratako/Oumuamua-7b-instruct-v2-RP

Oumuamua 7B Instruct V2 RP Parameters and Internals

Model Type

text generation, instruction following, role-play

Supported Languages

ja (Japanese)

Training Details

Data Sources:

Aratako/Rosebleu-1on1-Dialogues, Aratako/LimaRP-augmented-ja-karakuri, Aratako/Bluemoon_Top50MB_Sorted_Fixed_ja, grimulkan/LimaRP-augmented, SicariusSicariiStuff/Bluemoon_Top50MB_Sorted_Fixed, OmniAICreator/Japanese-Roleplay, OmniAICreator/Japanese-Roleplay-Dialogues

Methodology:

The model was fine-tuned using LoRA on role-play datasets. The training is conducted in two stages, first with lower-quality datasets and then with higher-quality datasets.

Context Length:

4096

Hardware Used:

A6000x4

Input Output

Input Format:

Chat with role-play instructions and context.

Accepted Modalities:

text

Output Format:

Role-play responses

Performance Tips:

End each turn of assistant response with an EOS token for multi-turn dialogues.

LLM Name	Oumuamua 7B Instruct V2 RP
Repository 🤗	https://huggingface.co/Aratako/Oumuamua-7b-instruct-v2-RP
Model Size	7b
Required VRAM	14.6 GB
Updated	2026-08-24
Maintainer	Aratako
Model Type	mistral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-3 4.9 GB: 2-of-3 4.8 GB: 3-of-3
Supported Languages	ja
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	42800
Torch Data Type	bfloat16

Rank the Oumuamua 7B Instruct V2 RP 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

Best Alternatives to Oumuamua 7B Instruct V2 RP

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
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
... Summarize 64K QLoRANET Merged	128K / 4.1 GB	10	0
...1 Summarize 64K LoRANET Merged	128K / 14.4 GB	13	0
Mistral 7B Instruct V0.2	32K / 14.4 GB	1115337	3184
Mistral 7B Instruct V0.1	32K / 14.4 GB	253629	1846
Mistral 7B Instruct V0.2	32K / 14.4 GB	1338	0
Lexi Coder V5.1	32K / 14.5 GB	197	0

Note: green Score (e.g. "73.2") means that the model is better than Aratako/Oumuamua-7b-instruct-v2-RP.