Instructions to use amkyawdev/myanmar-ghost with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use amkyawdev/myanmar-ghost with Transformers:

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

pipe = pipeline("text-generation", model="amkyawdev/myanmar-ghost")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("amkyawdev/myanmar-ghost", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use amkyawdev/myanmar-ghost with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/amkyawdev/myanmar-ghost

SGLang

How to use amkyawdev/myanmar-ghost 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 "amkyawdev/myanmar-ghost" \
    --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": "amkyawdev/myanmar-ghost",
		"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 "amkyawdev/myanmar-ghost" \
        --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": "amkyawdev/myanmar-ghost",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use amkyawdev/myanmar-ghost with Docker Model Runner:
```
docker model run hf.co/amkyawdev/myanmar-ghost
```

myanmar-ghost

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from setuptools import setup, find_packages

with open("README.md", "r", encoding="utf-8") as fh:
    long_description = fh.read()

setup(
    name="myanmar-ghost",
    version="1.0.0",
    author="Aung Myo Kyaw",
    author_email="amkyawdev@example.com",
    description="Advanced Myanmar Language Understanding Model with Multi-Modal Fusion",
    long_description=long_description,
    long_description_content_type="text/markdown",
    url="https://huggingface.co/amkyawdev/Myanmar-Ghost-Instruct",
    packages=find_packages(where="src"),
    package_dir={"": "src"},
    classifiers=[
        "Development Status :: 4 - Beta",
        "Intended Audience :: Developers",
        "Intended Audience :: Science/Research",
        "License :: OSI Approved :: Apache Software License",
        "Programming Language :: Python :: 3",
        "Programming Language :: Python :: 3.10",
        "Programming Language :: Python :: 3.11",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Topic :: Text Processing :: Linguistic",
    ],
    python_requires=">=3.10",
    install_requires=[
        "torch>=2.0.0",
        "transformers>=4.35.0",
        "datasets>=2.14.0",
        "librosa>=0.10.0",
    ],
    extras_require={
        "dev": [
            "pytest>=7.4.0",
            "black>=23.0.0",
            "isort>=5.12.0",
        ],
        "xai": [
            "shap>=0.42.0",
            "lime>=0.3.0",
        ],
        "federated": [
            "flwr>=1.5.0",
        ],
    },
)