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 α‘αα½αΎααΊαΈαααΊααΎααΊαααΊ αααΊαΈαα½αΎααΊαα»ααΊ
α‘αα½αΎααΊαΈ Label αα»α¬αΈ
1. Positive (α‘ααΌα―ααα±α¬) β
- αααΉααα¬: ααα―αΈαα¬αΈαα±α¬ αα»α±αΈαα°αΈαααΊααΎα―α αααΊαΉααα¬
- α₯ααα¬:
- "αα»α±αΈαα°αΈαα«"
- "α‘αααΊαΈαα»α±αΈαα°αΈαααΊαα«αααΊ"
- "αααΊαΉααα¬αα«"
2. Negative (α‘ααΎα―ααΊααα±α¬) β
- αααΉααα¬: ααα»α±αααΊααΌααΊαΈα αα±α«αα αααΊαΈαα¬ααΎα―
- α₯ααα¬:
- "αα»α±αΈαα°αΈαα«" (ααα±α¬αΊαααΊααΌα αΊααα―ααΊ)
- "αα¬ααΌα±α¬αα·αΊαααΊαΈααα"
3. Neutral (α‘αααΊα‘αααΊ) β
- αααΉααα¬: ααααΊαΈα‘αα»ααΊα‘αααΊαα¬ααΌα αΊ
- α₯ααα¬:
- "αα»α±αΈαα°αΈαα«" (ααα―αΈααΎααΊαΈα α½α¬ααΌα±α¬αααΊ)
4. Sarcastic (ααα±α¬αΊααΌααΊαΈ) π€¨
- αααΉααα¬: α‘ααααΉαα«ααΊαα½α±α·α ααα±α¬αΊααΌααΊαΈ
- α₯ααα¬:
- "αα»α±αΈαα°αΈαα«αα»α¬" (α‘ααα―ααΊααΎααΊαΈαααΊ)
Intensity (α‘α¬αΈααΌαα―ααΊααΎα―)
| Level | Score | Description |
|---|---|---|
| Very Low | 0.1-0.2 | α‘α¬αΈαααΊαΈαα±α¬ ααα―ααΊαΈααΆα· |
| Low | 0.3-0.4 | αα―αΆααΎααΊ |
| Medium | 0.5-0.6 | ααΌααΊαΈααΌ |
| High | 0.7-0.8 | α‘αα½ααΊααΌααΊαΈ |
| Very High | 0.9-1.0 | α‘αα°αΈααΌααΊαΈ |
Prosody (α‘ααΆ) ααα―α αα―ααΊαααΊ
- Pitch (α‘ααΆα‘αααα·αΊα‘ααΌαα·αΊ): ααΌαα·αΊ = α αααΊααΎα―ααΊααΎα¬αΈα αααα·αΊ = ααΌααα·αΊαα±α¬
- Speed (α‘ααΌααΊααΎα―ααΊαΈ): ααΌααΊ = αααΊαΈαα¬α ααΎα±αΈ = αα»α±α¬αΊαα«
- Pause (αα¬αΈαα»αααΊ): ααΎααΊ = α ααΊαΈα α¬αΈα αααΎα = α‘ααα―ααα―αα±α¬
ααΎααΊα α―
- Text ααΎαα·αΊ Audio prosody ααΎα αΊαα―αα―αΆαΈααα― ααΌαα·αΊαα«
- Context ααα― αααααΌα―αα« (α‘αααΊα αα¬αΈααΌα±α¬αα»ααΊ)
- ααΆααααΌα αΊαα«α "Confidence" αααα·αΊα α½α¬ αααΊααΎααΊαα«