What are the hardware requirements for Reverse Instruct?

Reverse Instruct requires approximately 27 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 Reverse Instruct and how large is it?

Reverse Instruct is developed by vikp. 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 Reverse Instruct?

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

Reverse Instruct by vikp — VRAM 27GB, 32K context

Name: Reverse Instruct
Author: vikp

Reverse Instruct is an open-source language model by vikp. Features: LLM, VRAM: 27GB, Context: 32K, License: cc, Instruction-Based, LLM Explorer Score: 0.08.

Custom code Dataset:vikp/reverse instruct Endpoints compatible Instruct Llama Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/vikp/reverse_instruct

Reverse Instruct Parameters and Internals

Model Type

Text Generation

Use Cases

Primary Use Cases:

Instruction generation for text, Labeling unlabeled datasets

Limitations:

Undertrained on code

Training Details

Data Sources:

vikp/reverse_instruct

Context Length:

32000

LLM Name	Reverse Instruct
Repository 🤗	https://huggingface.co/vikp/reverse_instruct
Required VRAM	27 GB
Updated	2026-08-05
Maintainer	vikp
Model Type	llama
Instruction-Based	Yes
Model Files	9.9 GB: 1-of-3 9.9 GB: 2-of-3 7.2 GB: 3-of-3
Model Architecture	LlamaForCausalLM
License	cc
Context Length	32768
Model Max Length	32768
Transformers Version	4.31.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32001
Torch Data Type	float32

Rank the Reverse Instruct 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 Reverse Instruct

Best Alternatives	Context / RAM	Downloads	Likes
Etri Ones Solar	4K / 42.9 GB	50	0
Phi 3 Orpo V8.16	4K / 7.6 GB	7	0
Tinyllama Python	4K / 2.2 GB	13	2
Small Instruct	4K / 2.9 GB	10	1
Taiwan LLaMa V1.0	4K / 26 GB	35	78
Taiwan LLaMa V0.0	4K / 26 GB	14	1
Taiwan LLaMa V0.9	4K / 26 GB	13	0
Llama2 Ja Small Instruct	2K / 1.7 GB	5	1
Kolong Llama V0.1	2K / 13.7 GB	7	0
...ama Miniguanaco Instruct 121v2	2K / 2.2 GB	11	0

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