Instructions to use michaelw37/mc36 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use michaelw37/mc36 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="michaelw37/mc36")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("michaelw37/mc36")
model = AutoModelForCausalLM.from_pretrained("michaelw37/mc36", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use michaelw37/mc36 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "michaelw37/mc36"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "michaelw37/mc36",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/michaelw37/mc36

SGLang

How to use michaelw37/mc36 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 "michaelw37/mc36" \
    --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": "michaelw37/mc36",
		"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 "michaelw37/mc36" \
        --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": "michaelw37/mc36",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use michaelw37/mc36 with Docker Model Runner:
```
docker model run hf.co/michaelw37/mc36
```

mc36

Commit History

Upload LlamaForCausalLM

f51080b
verified

Michael commited on Apr 19, 2024

Upload tokenizer

b3fc6f8
verified

Michael commited on Apr 19, 2024

initial commit

4bc97a2
verified

Michael commited on Apr 19, 2024

Commit History

Upload LlamaForCausalLM f51080b verified

Upload tokenizer b3fc6f8 verified

initial commit 4bc97a2 verified

Upload LlamaForCausalLM

f51080b
verified

Upload tokenizer

b3fc6f8
verified

initial commit

4bc97a2
verified