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

Libraries

How to use TroyDoesAI/MermaidMistral with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TroyDoesAI/MermaidMistral")
model = AutoModelForCausalLM.from_pretrained("TroyDoesAI/MermaidMistral")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TroyDoesAI/MermaidMistral with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/TroyDoesAI/MermaidMistral

SGLang

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

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

TroyDoesAI commited on Jan 9, 2024

Commit

339d45e

1 Parent(s): c1002a1

Adding an Example Prompt using TextGenerationWebUI to help users get the best output. always have response start with ```mermaid graph TB;

Browse files

Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

### Instruction:
Create the Mermaid Diagram for the following code:

### Input:
# Simple Calculator
def add(x, y):
return x + y

def subtract(x, y):
return x - y

def multiply(x, y):
return x * y

def divide(x, y):
if y != 0:
return x / y
else:
return "Cannot divide by zero"

def main():
num1 = float(input("Enter first number: "))
num2 = float(input("Enter second number: "))
operation = input("Enter operation (+, -, *, /): ")

if operation == "+":
result = add(num1, num2)
elif operation == "-":
result = subtract(num1, num2)
elif operation == "*":
result = multiply(num1, num2)
elif operation == "/":
result = divide(num1, num2)
else:
result = "Invalid operation"

print(f"Result: {result}")

### Response:
```mermaid
graph TB;

Files changed (1) hide show

Example_Using_TextGenerationWebUI_Notebook.png +0 -0

Example_Using_TextGenerationWebUI_Notebook.png ADDED Viewed