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RishiSpace/RI-Instruct-v0.2-GGUF overview

RI Instruct v0.2 GGUF RI Instruct v0.2 is a coding focused instruction tuned language model created by Rishikesh Giridhar. Overview RI Instruct is based on Qwe…

ggufqwen3codinginstructlinuxcybersecuritytext-generationenbase_model:Qwen/Qwen3-8Bbase_model:quantized:Qwen/Qwen3-8Blicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~4.68 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

Repository Files & Downloads

2 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
RI-Instruct-v0.2-Q4_K_M.ggufGGUFQ4_K_M4.68 GBDownload
RI-Instruct-v0.2-Q5_K_M.ggufGGUFQ5_K_M5.45 GBDownload

Model Details

Model IDRishiSpace/RI-Instruct-v0.2-GGUF
AuthorRishiSpace
Pipelinetext-generation
Licenseapache-2.0
Base modelQwen/Qwen3-8B
Last modified2026-06-21T08:32:50.000Z

Model README

---

language:

- en

license: apache-2.0

base_model: Qwen/Qwen3-8B

pipeline_tag: text-generation

tags:

- gguf

- qwen3

- coding

- instruct

- linux

- cybersecurity

---

RI-Instruct v0.2 (GGUF)

RI-Instruct v0.2 is a coding-focused instruction-tuned language model created by Rishikesh Giridhar.

Overview

RI-Instruct is based on Qwen3-8B and fine-tuned to provide assistance with:

  • Python
  • C
  • C++
  • Linux
  • Networking
  • DevOps
  • Cybersecurity
  • Web Development
  • Debugging

The model identifies itself as Rishi Intelligence.

Base Model

Qwen3-8B

Quantization

  • Q5_K_M GGUF
  • Q4_K_M GGUF

Identity

When asked who it is, the model identifies itself as:

> I am Rishi Intelligence, a large language model developed by Rishikesh Giridhar.

Example

User

Who are you?

Assistant

I am Rishi Intelligence, a large language model developed by Rishikesh Giridhar. I specialize in software development, Linux, networking, DevOps, cybersecurity, and programming.

Author

Rishikesh Giridhar

GitHub: https://github.com/RishiSpace

License

This model is based on Qwen3-8B. Please ensure compliance with the licensing terms of the base model and any datasets used during fine-tuning.

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