Text Generation
Transformers
Burmese
English
myanmar
burmese
llm
chat
instruction-following
conversational
autoregressive
Instructions to use amkyawdev/myanmar-ghost with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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", dtype="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
| """File I/O utilities for Myanmar Ghost project.""" | |
| import json | |
| import os | |
| from pathlib import Path | |
| from typing import Any, Dict, List, Optional | |
| import pandas as pd | |
| import yaml | |
| def load_json(path: str) -> Any: | |
| """Load JSON file.""" | |
| with open(path, "r", encoding="utf-8") as f: | |
| return json.load(f) | |
| def save_json(data: Any, path: str, indent: int = 2) -> None: | |
| """Save data to JSON file.""" | |
| Path(path).parent.mkdir(parents=True, exist_ok=True) | |
| with open(path, "w", encoding="utf-8") as f: | |
| json.dump(data, f, indent=indent, ensure_ascii=False) | |
| def load_yaml(path: str) -> Dict: | |
| """Load YAML file.""" | |
| with open(path, "r", encoding="utf-8") as f: | |
| return yaml.safe_load(f) | |
| def save_yaml(data: Dict, path: str) -> None: | |
| """Save data to YAML file.""" | |
| Path(path).parent.mkdir(parents=True, exist_ok=True) | |
| with open(path, "w", encoding="utf-8") as f: | |
| yaml.dump(data, f, allow_unicode=True, default_flow_style=False) | |
| def load_jsonl(path: str) -> List[Dict]: | |
| """Load JSONL file (one JSON object per line).""" | |
| data = [] | |
| with open(path, "r", encoding="utf-8") as f: | |
| for line in f: | |
| if line.strip(): | |
| data.append(json.loads(line)) | |
| return data | |
| def save_jsonl(data: List[Dict], path: str) -> None: | |
| """Save data to JSONL file.""" | |
| Path(path).parent.mkdir(parents=True, exist_ok=True) | |
| with open(path, "w", encoding="utf-8") as f: | |
| for item in data: | |
| f.write(json.dumps(item, ensure_ascii=False) + "\n") | |
| def load_csv(path: str) -> pd.DataFrame: | |
| """Load CSV file as DataFrame.""" | |
| return pd.read_csv(path) | |
| def save_csv(df: pd.DataFrame, path: str, index: bool = False) -> None: | |
| """Save DataFrame to CSV file.""" | |
| Path(path).parent.mkdir(parents=True, exist_ok=True) | |
| df.to_csv(path, index=index) | |
| def ensure_dir(path: str) -> Path: | |
| """Ensure directory exists.""" | |
| p = Path(path) | |
| p.mkdir(parents=True, exist_ok=True) | |
| return p | |
| def list_files( | |
| directory: str, | |
| pattern: str = "*", | |
| recursive: bool = False, | |
| ) -> List[Path]: | |
| """List files in directory matching pattern.""" | |
| p = Path(directory) | |
| if recursive: | |
| return list(p.rglob(pattern)) | |
| return list(p.glob(pattern)) | |
| def get_file_size(path: str) -> int: | |
| """Get file size in bytes.""" | |
| return os.path.getsize(path) | |
| def copy_file(src: str, dst: str) -> None: | |
| """Copy file from src to dst.""" | |
| import shutil | |
| Path(dst).parent.mkdir(parents=True, exist_ok=True) | |
| shutil.copy2(src, dst) | |
| def move_file(src: str, dst: str) -> None: | |
| """Move file from src to dst.""" | |
| import shutil | |
| Path(dst).parent.mkdir(parents=True, exist_ok=True) | |
| shutil.move(src, dst) | |
| def delete_file(path: str) -> None: | |
| """Delete file.""" | |
| Path(path).unlink(missing_ok=True) | |
| class ConfigManager: | |
| """Manage configuration files.""" | |
| def __init__(self, config_dir: str = "configs"): | |
| self.config_dir = Path(config_dir) | |
| def load(self, name: str, config_type: str = "yaml") -> Dict: | |
| """Load configuration by name.""" | |
| path = self.config_dir / f"{name}.{config_type}" | |
| if config_type == "yaml": | |
| return load_yaml(str(path)) | |
| elif config_type == "json": | |
| return load_json(str(path)) | |
| else: | |
| raise ValueError(f"Unsupported config type: {config_type}") | |
| def save(self, name: str, config: Dict, config_type: str = "yaml") -> None: | |
| """Save configuration by name.""" | |
| path = self.config_dir / f"{name}.{config_type}" | |
| if config_type == "yaml": | |
| save_yaml(config, str(path)) | |
| elif config_type == "json": | |
| save_json(config, str(path)) | |
| else: | |
| raise ValueError(f"Unsupported config type: {config_type}") | |
| if __name__ == "__main__": | |
| # Test file utilities | |
| print("File utilities loaded") | |
| print(f"Current directory: {Path.cwd()}") | |