Instructions to use amkyawdev/amkyaw-dev-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use amkyawdev/amkyaw-dev-v1 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="amkyawdev/amkyaw-dev-v1", filename="amkyaw-coder-1.5b-instruct.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 amkyawdev/amkyaw-dev-v1 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf amkyawdev/amkyaw-dev-v1 # Run inference directly in the terminal: llama-cli -hf amkyawdev/amkyaw-dev-v1
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf amkyawdev/amkyaw-dev-v1 # Run inference directly in the terminal: llama-cli -hf amkyawdev/amkyaw-dev-v1
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 amkyawdev/amkyaw-dev-v1 # Run inference directly in the terminal: ./llama-cli -hf amkyawdev/amkyaw-dev-v1
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 amkyawdev/amkyaw-dev-v1 # Run inference directly in the terminal: ./build/bin/llama-cli -hf amkyawdev/amkyaw-dev-v1
Use Docker
docker model run hf.co/amkyawdev/amkyaw-dev-v1
- LM Studio
- Jan
- Ollama
How to use amkyawdev/amkyaw-dev-v1 with Ollama:
ollama run hf.co/amkyawdev/amkyaw-dev-v1
- Unsloth Studio new
How to use amkyawdev/amkyaw-dev-v1 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 amkyawdev/amkyaw-dev-v1 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 amkyawdev/amkyaw-dev-v1 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for amkyawdev/amkyaw-dev-v1 to start chatting
- Pi new
How to use amkyawdev/amkyaw-dev-v1 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf amkyawdev/amkyaw-dev-v1
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": "amkyawdev/amkyaw-dev-v1" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use amkyawdev/amkyaw-dev-v1 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf amkyawdev/amkyaw-dev-v1
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 amkyawdev/amkyaw-dev-v1
Run Hermes
hermes
- Docker Model Runner
How to use amkyawdev/amkyaw-dev-v1 with Docker Model Runner:
docker model run hf.co/amkyawdev/amkyaw-dev-v1
- Lemonade
How to use amkyawdev/amkyaw-dev-v1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull amkyawdev/amkyaw-dev-v1
Run and chat with the model
lemonade run user.amkyaw-dev-v1-{{QUANT_TAG}}List all available models
lemonade list
Upload README.md with huggingface_hub
Browse files
README.md
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# amkyawdev/amkyaw-dev-v1
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## Model Overview
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- **Model Name**: amkyaw-coder-1.5b-instruct
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- **Type**: Code Generation / Instruction Following
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- **Size**: 1.5B parameters
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- **Format**: GGUF (quantized)
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## Quick Start
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```bash
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# Run the model
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ollama run amkyawdev/amkyaw-dev-v1
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# Or run with specific tag
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ollama run amkyawdev/amkyaw-dev-v1:latest
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```
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## Features
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- Code generation
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- Instruction following
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- Burmese language support
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- English language support
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## System Requirements
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- Ollama installed
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- At least 2GB RAM available
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- No GPU required (runs on CPU)
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## Configuration
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| Parameter | Value |
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|-----------|-------|
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| Temperature | 0.8 |
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| Top P | 0.9 |
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| Top K | 40 |
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| Context Length | 4096 |
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## Usage Examples
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```python
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import ollama
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response = ollama.generate(
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model='amkyawdev/amkyaw-dev-v1',
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prompt='Write a Python function to calculate factorial'
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)
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print(response['response'])
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```
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## License
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See [Hugging Face](https://huggingface.co/amkyawdev/amkyaw-dev-v1) for license information.
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## Troubleshooting
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If you encounter issues:
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1. Make sure Ollama is running: `ollama serve`
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2. Check model is installed: `ollama list`
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3. Try restarting Ollama: `pkill ollama && ollama serve`
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