---

license: apache-2.0

base_model: CohereLabs/North-Mini-Code-1.0

tags:

- gguf

- llama.cpp

- cohere

- code

- moe

- quantized

- north-mini-code

pipeline_tag: text-generation

language:

- en

---

North-Mini-Code-1.0-GGUF

GGUF conversions and quantizations of CohereLabs/North-Mini-Code-1.0 for use with:

• llama.cpp
• LM Studio
• Ollama
• Jan
• KoboldCpp
• Text Generation WebUI
• Open WebUI
• Other GGUF-compatible runtimes

---

About the Model

North-Mini-Code-1.0 is a code-focused Mixture-of-Experts (MoE) model released by CohereLabs.

This repository provides ready-to-use GGUF conversions for local inference across a range of hardware configurations.

---

Available Files

Full Precision

• North-Mini-Code-1.0-F16.gguf

Quantized Versions

• North-Mini-Code-1.0-Q4_K_M.gguf
• North-Mini-Code-1.0-Q5_K_M.gguf
• North-Mini-Code-1.0-Q6_K.gguf
• North-Mini-Code-1.0-Q8_0.gguf

---

Recommended Quantization

For most users:

North-Mini-Code-1.0-Q4_K_M.gguf

It offers the best balance of:

• Quality
• Memory usage
• Inference speed

If you have more available RAM/VRAM, consider:

North-Mini-Code-1.0-Q5_K_M.gguf

or

North-Mini-Code-1.0-Q6_K.gguf

for slightly higher output quality.

---

Approximate File Sizes

F16      ~60+ GB
Q4_K_M   ~20 GB
Q5_K_M   ~23 GB
Q6_K     ~27 GB
Q8_0     ~34 GB

Actual sizes may vary slightly depending on conversion tooling versions.

---

Usage

llama.cpp

Prompt mode:

./llama-cli \
  -m North-Mini-Code-1.0-Q4_K_M.gguf \
  -p "Write a Python function that reverses a linked list."

Chat mode:

./llama-cli \
  -m North-Mini-Code-1.0-Q4_K_M.gguf \
  -cnv

---

LM Studio

1. Download your preferred GGUF file.
2. Open LM Studio.
3. Import the model.
4. Start chatting.

---

Ollama

Create a Modelfile:

FROM North-Mini-Code-1.0-Q4_K_M.gguf

Create the model:

ollama create north-mini-code -f Modelfile

Run it:

ollama run north-mini-code

---

Hardware Recommendations

Q4_K_M

Recommended minimum:

24 GB RAM

Q5_K_M

Recommended minimum:

32 GB RAM

Q6_K

Recommended minimum:

32-40 GB RAM

Q8_0

Recommended minimum:

48+ GB RAM

F16

Recommended minimum:

80+ GB RAM

---

Prompting Tips

This model is optimized for programming-related tasks.

Example prompts:

Implement a fast Rust HTTP server.

Explain this C++ compiler error.

Write comprehensive unit tests for the following Python code.

Convert this JavaScript function to TypeScript.

Optimize this SQL query.

---

Base Model

Base model:

CohereLabs/North-Mini-Code-1.0

All training, architecture, benchmarks, licensing terms, and usage restrictions belong to the original model authors.

Please refer to the original repository for official documentation and licensing information.

---

Conversion Details

Converted using:

llama.cpp

Generated quantizations:

F16
Q4_K_M
Q5_K_M
Q6_K
Q8_0

A tokenizer compatibility workaround was applied during conversion to support current GGUF conversion tooling.

---

Credits

• Base Model: CohereLabs
• GGUF Conversion & Quantization: NANI-Nithin
• Tooling: llama.cpp

---

Repository

👉 https://huggingface.co/NANI-Nithin/north-mini-code-gguf