Instructions to use WYNN747/burmese-coder-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use WYNN747/burmese-coder-4b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="WYNN747/burmese-coder-4b")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("WYNN747/burmese-coder-4b", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use WYNN747/burmese-coder-4b 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 WYNN747/burmese-coder-4b:BF16
# Run inference directly in the terminal:
llama cli -hf WYNN747/burmese-coder-4b:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf WYNN747/burmese-coder-4b:BF16
# Run inference directly in the terminal:
llama cli -hf WYNN747/burmese-coder-4b:BF16

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 WYNN747/burmese-coder-4b:BF16
# Run inference directly in the terminal:
./llama-cli -hf WYNN747/burmese-coder-4b:BF16

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 WYNN747/burmese-coder-4b:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf WYNN747/burmese-coder-4b:BF16

Use Docker

docker model run hf.co/WYNN747/burmese-coder-4b:BF16

Llama new
LM Studio
Jan

vLLM

How to use WYNN747/burmese-coder-4b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "WYNN747/burmese-coder-4b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WYNN747/burmese-coder-4b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/WYNN747/burmese-coder-4b:BF16

SGLang

How to use WYNN747/burmese-coder-4b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "WYNN747/burmese-coder-4b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WYNN747/burmese-coder-4b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "WYNN747/burmese-coder-4b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WYNN747/burmese-coder-4b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use WYNN747/burmese-coder-4b with Ollama:
```
ollama run hf.co/WYNN747/burmese-coder-4b:BF16
```
Unsloth Desktop
Docker Model Runner
How to use WYNN747/burmese-coder-4b with Docker Model Runner:
```
docker model run hf.co/WYNN747/burmese-coder-4b:BF16
```

Lemonade

How to use WYNN747/burmese-coder-4b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull WYNN747/burmese-coder-4b:BF16

Run and chat with the model

lemonade run user.burmese-coder-4b-BF16

List all available models

lemonade list

Atomic Chat

WYNN747 commited on Apr 12

Commit

f52bb87

verified ·

1 Parent(s): 2c97b04

Update README.md

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README.md CHANGED Viewed

@@ -12,7 +12,6 @@ datasets:
 tags:
   - burmese
   - myanmar
-  - burmese-language-ai
   - code-generation
   - coding-assistant
   - low-resource-language
@@ -20,12 +19,11 @@ tags:
   - gemma-3
   - dpo
   - sft
-  - ollama
 ---
 # Burmese Coder 🏹🔥
-Burmese-Coder-4B is a Burmese-language coding model created by Dr. Wai Yan Nyein Naing, a Myanmar AI researcher focused on Burmese language AI and low-resource LLMs. Fine-tuned from Gemma 3 4B, it is designed for code generation, technical explanation, and reduced mixed-language output for Burmese-speaking developers and researchers. In evaluation, Burmese-Coder-4B matched the base model on Pass@1 while improving Burmese-language quality and sharply reducing mixed-language penalties.
 **Author:** Dr. Wai Yan Nyein Naing
 **Focus:** Burmese code generation + technical explanation

 tags:
   - burmese
   - myanmar
   - code-generation
   - coding-assistant
   - low-resource-language
   - gemma-3
   - dpo
   - sft
 ---
 # Burmese Coder 🏹🔥
+Burmese-Coder-4B is a Burmese-language coding model created by Dr. Wai Yan Nyein Naing, a Myanmar AI researcher focused on Burmese language AI and low-resource LLMs. Fine-tuned from Gemma 3 4B, it is designed for code generation, technical explanation, and reduced mixed-language output for Burmese-speaking developers and researchers. In evaluation, it matched the base model on Pass@1 while improving Burmese-language quality and sharply reducing mixed-language penalties.
 **Author:** Dr. Wai Yan Nyein Naing
 **Focus:** Burmese code generation + technical explanation