Instructions to use mykor/Midm-2.0-Base-Instruct-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mykor/Midm-2.0-Base-Instruct-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="mykor/Midm-2.0-Base-Instruct-gguf",
	filename="Midm-2.0-Base-Instruct-BF16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mykor/Midm-2.0-Base-Instruct-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

Use Docker

docker model run hf.co/mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use mykor/Midm-2.0-Base-Instruct-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mykor/Midm-2.0-Base-Instruct-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mykor/Midm-2.0-Base-Instruct-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

Ollama
How to use mykor/Midm-2.0-Base-Instruct-gguf with Ollama:
```
ollama run hf.co/mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M
```

Unsloth Studio

How to use mykor/Midm-2.0-Base-Instruct-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for mykor/Midm-2.0-Base-Instruct-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for mykor/Midm-2.0-Base-Instruct-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for mykor/Midm-2.0-Base-Instruct-gguf to start chatting

How to use mykor/Midm-2.0-Base-Instruct-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use mykor/Midm-2.0-Base-Instruct-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use mykor/Midm-2.0-Base-Instruct-gguf with Docker Model Runner:
```
docker model run hf.co/mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M
```

Lemonade

How to use mykor/Midm-2.0-Base-Instruct-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mykor/Midm-2.0-Base-Instruct-gguf:Q4_K_M

Run and chat with the model

lemonade run user.Midm-2.0-Base-Instruct-gguf-Q4_K_M

List all available models

lemonade list

Bingsu commited on Jul 10, 2025

Commit

30bbc02

verified ·

1 Parent(s): 595841f

Update README.md

Browse files

Files changed (1) hide show

README.md +15 -16

README.md CHANGED Viewed

@@ -1,18 +1,17 @@
----
-license: mit
-language:
-- en
-- ko
-tags:
-- KT
-- K-intelligence
-- Mi:dm
-inference: true
-pipeline_tag: text-generation
-library_name: transformers
-base_model:
-- K-intelligence/Midm-2.0-Base-Instruct
----
 <p align="center">
@@ -23,7 +22,7 @@ base_model:
 <p align="center">
 🤗 <a href="https://huggingface.co/collections/K-intelligence/mi-dm-20-6866406c301e5f45a6926af8">Mi:dm 2.0 Models</a> |
-📜 <a href="https://github.com/K-intelligence-Midm/Midm-2.0/blob/main/Mi_dm-2_0_technical_report.pdf">Mi:dm 2.0 Technical Report</a> |
 📕 Mi:dm 2.0 Technical Blog*
 </p>

+---
+license: mit
+language:
+- en
+- ko
+tags:
+- KT
+- K-intelligence
+- Mi:dm
+inference: true
+pipeline_tag: text-generation
+base_model:
+- K-intelligence/Midm-2.0-Base-Instruct
+---
 <p align="center">
 <p align="center">
 🤗 <a href="https://huggingface.co/collections/K-intelligence/mi-dm-20-6866406c301e5f45a6926af8">Mi:dm 2.0 Models</a> |
+📜 <a href="https://github.com/K-intelligence-Midm/Midm-2.0/blob/main/Mi_dm2_0_technical_report.pdf">Mi:dm 2.0 Technical Report</a> |
 📕 Mi:dm 2.0 Technical Blog*
 </p>