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
```

amkyawdev commited on Jul 10

Commit

ba01b1a

verified ·

1 Parent(s): 9574bbb

Update to LLM model - text-generation pipeline

Browse files

Files changed (1) hide show

README.md +19 -17

README.md CHANGED Viewed

@@ -1,18 +1,18 @@
 ---
 language:
-    - my
-    - en
-    license: apache-2.0
-    library_name: transformers
-    pipeline_tag: text-generation
-    tags:
-        - myanmar
-        - burmese
-        - llm
-        - chat
-        - instruction-following
-        ---
 # Myanmar Ghost
 **Advanced Myanmar Language Model (LLM)**
@@ -45,10 +45,12 @@ print(tokenizer.decode(outputs[0]))
 ## Training Data
-- myanmar-v3-clean: 877K
-- burme-coder-max: 1M
-- mm-llm-coder-agent: 4M
-- alpaca-myanmar: 91K
 ## License

 ---
 language:
+- my
+- en
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- myanmar
+- burmese
+- llm
+- chat
+- instruction-following
+---
 # Myanmar Ghost
 **Advanced Myanmar Language Model (LLM)**
 ## Training Data
+| Dataset | Samples |
+|---------|---------|
+| myanmar-v3-clean | 877K |
+| burme-coder-max | 1M |
+| mm-llm-coder-agent | 4M |
+| alpaca-myanmar | 91K |
 ## License