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
| # π²π² Myanmar Ghost | |
| ## ααααΊαααΊ | |
| Myanmar Ghost αααΊ ααΌααΊαα¬α α¬αα¬αΈα‘αααΊαα½αα·αΊααα―ααΌααΊαΈ (Sentiment Analysis) α‘αα½ααΊ α‘ααα·αΊααΌαα·αΊ AI Model αα αΊαα―ααΌα αΊαα«αααΊα | |
| ### α‘ααααα―ααΊαα±α¬ααΊαα»ααΊαα»α¬αΈ | |
| - **Multi-Modal Fusion** - α‘ααΆ + α α¬αα¬αΈ αα±α«ααΊαΈα ααΊααΌααΊαΈ | |
| - **Active Learning** - αααα±α¬ααΊαα±α¬ α‘αα½αΎααΊαΈαααΊααΎααΊααΌααΊαΈ | |
| - **Federated Learning** - Privacy-preserving training | |
| - **Explainable AI** - SHAP/LIME ααΌαα·αΊ ααΎααΊαΈααΌααΌααΊαΈ | |
| - **Data Augmentation** - Adversarial augmentation | |
| ## αααΊαααΊααΌααΊαΈ | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| ## α‘αα―αΆαΈααΌα―αα―αΆ | |
| ### Training | |
| ```bash | |
| python src/models/train.py \ | |
| --train_data data/processed/splits/train.csv \ | |
| --output_dir outputs/models | |
| ``` | |
| ### Evaluation | |
| ```bash | |
| python src/models/evaluate.py \ | |
| --model_path outputs/models/best_model.pt \ | |
| --data_path data/processed/splits/test.csv | |
| ``` | |
| ### API Run | |
| ```bash | |
| uvicorn deployment.api.app:app --host 0.0.0.0 --port 8000 | |
| ``` | |
| ## Project Structure | |
| ``` | |
| Myanmar-Ghost/ | |
| βββ src/ | |
| β βββ data_processing/ # Data processing | |
| β βββ annotation/ # Annotation tools | |
| β βββ models/ # Model implementations | |
| β βββ federated/ # Federated learning | |
| β βββ xai/ # Explainable AI | |
| β βββ augmentation/ # Data augmentation | |
| β βββ utils/ # Utilities | |
| βββ configs/ # Configuration | |
| βββ data/ # Data directory | |
| βββ tests/ # Unit tests | |
| βββ docs/ # Documentation | |
| ``` | |
| ## License | |
| Apache 2.0 | |
| ## Author | |
| Aung Myo Kyaw | |
| https://huggingface.co/amkyawdev | |