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
| # Dataset Configuration - Base | |
| name: myanmar_ghost_base | |
| version: 1.0.0 | |
| # Data paths | |
| data: | |
| raw_dir: data/raw | |
| processed_dir: data/processed | |
| augmented_dir: data/augmented | |
| annotations_dir: data/annotations | |
| # Processing settings | |
| processing: | |
| audio: | |
| sample_rate: 16000 | |
| n_fft: 512 | |
| hop_length: 160 | |
| n_mels: 80 | |
| text: | |
| max_length: 512 | |
| min_length: 1 | |
| remove_non_myanmar: false | |
| # Split ratios | |
| splits: | |
| train: 0.8 | |
| val: 0.1 | |
| test: 0.1 | |
| stratify: true | |
| # Label scheme | |
| labels: | |
| sentiment: | |
| - negative | |
| - neutral | |
| - positive | |
| - sarcastic | |
| # Data augmentation | |
| augmentation: | |
| enabled: true | |
| synonym_replacement: | |
| enabled: true | |
| probability: 0.3 | |
| perturbation: | |
| enabled: true | |
| probability: 0.1 | |
| types: | |
| - char_swap | |
| - word_swap | |
| - keyboard_typo | |