Instructions to use sthaps/Maincoder-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sthaps/Maincoder-1B with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("sthaps/Maincoder-1B", dtype="auto")

llama-cpp-python

How to use sthaps/Maincoder-1B with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="sthaps/Maincoder-1B",
	filename="Maincoder-1B-q2_k.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use sthaps/Maincoder-1B with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf sthaps/Maincoder-1B:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf sthaps/Maincoder-1B:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf sthaps/Maincoder-1B:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf sthaps/Maincoder-1B: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 sthaps/Maincoder-1B:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf sthaps/Maincoder-1B: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 sthaps/Maincoder-1B:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf sthaps/Maincoder-1B:Q4_K_M

Use Docker

docker model run hf.co/sthaps/Maincoder-1B:Q4_K_M

LM Studio
Jan
Ollama
How to use sthaps/Maincoder-1B with Ollama:
```
ollama run hf.co/sthaps/Maincoder-1B:Q4_K_M
```

Unsloth Studio new

How to use sthaps/Maincoder-1B 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 sthaps/Maincoder-1B 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 sthaps/Maincoder-1B to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for sthaps/Maincoder-1B to start chatting

Pi new

How to use sthaps/Maincoder-1B with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf sthaps/Maincoder-1B: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": "sthaps/Maincoder-1B:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use sthaps/Maincoder-1B with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf sthaps/Maincoder-1B: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 sthaps/Maincoder-1B:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use sthaps/Maincoder-1B with Docker Model Runner:
```
docker model run hf.co/sthaps/Maincoder-1B:Q4_K_M
```

Lemonade

How to use sthaps/Maincoder-1B with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull sthaps/Maincoder-1B:Q4_K_M

Run and chat with the model

lemonade run user.Maincoder-1B-Q4_K_M

List all available models

lemonade list

sthaps commited on Jan 4

Commit

57b9747

verified ·

1 Parent(s): 9c98b4f

Update Model Card

Browse files

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README.md +30 -0

README.md ADDED Viewed

	@@ -0,0 +1,30 @@

+# Maincoder-1B - GGUF
+## About
+This repository contains GGUF weights for [Maincode/Maincoder-1B](https://huggingface.co/Maincode/Maincoder-1B).
+For a convenient overview and download list, visit our [model page](https://huggingface.co/sthaps/Maincoder-1B).
+## Usage
+If you are unsure how to use GGUF files, refer to the [llama.cpp documentation](https://github.com/ggerganov/llama.cpp) for more details.
+### Llama.cpp CLI
+```bash
+./llama-cli -m Maincoder-1B-q4_k_m.gguf -p "Hello!"
+```
+## Provided Quants
+(sorted by size, not necessarily quality)
+| Link | Type | Size/GB | Notes |
+| :--- | :--- | :---: | :--- |
+| [GGUF](https://huggingface.co/sthaps/Maincoder-1B/blob/main/Maincoder-1B-q2_k.gguf) | q2_k | 0.46 | very low quality, for testing |
+| [GGUF](https://huggingface.co/sthaps/Maincoder-1B/blob/main/Maincoder-1B-q3_k_m.gguf) | q3_k_m | 0.54 |  |
+| [GGUF](https://huggingface.co/sthaps/Maincoder-1B/blob/main/Maincoder-1B-q4_0.gguf) | q4_0 | 0.60 |  |
+| [GGUF](https://huggingface.co/sthaps/Maincoder-1B/blob/main/Maincoder-1B-q4_k_m.gguf) | q4_k_m | 0.63 | recommended, good balance |
+| [GGUF](https://huggingface.co/sthaps/Maincoder-1B/blob/main/Maincoder-1B-q5_k_m.gguf) | q5_k_m | 0.71 |  |
+| [GGUF](https://huggingface.co/sthaps/Maincoder-1B/blob/main/Maincoder-1B-q8_0.gguf) | q8_0 | 1.02 | near-full precision |
+## Thanks
+Special thanks to the `llama.cpp` team for their amazing work.