Instructions to use microsoft/DialoGPT-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/DialoGPT-large with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
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 microsoft/DialoGPT-large with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/microsoft/DialoGPT-large

SGLang

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

Docker Model Runner
How to use microsoft/DialoGPT-large with Docker Model Runner:
```
docker model run hf.co/microsoft/DialoGPT-large
```

"There was an inference error: unknown error: can only concatenate str (not \"dict\") to str"

#21

by breisa - opened May 10, 2024

Discussion

breisa

May 10, 2024

I'm trying to use the inference API, but I'm getting this error:

"There was an inference error: unknown error: can only concatenate str (not \"dict\") to str"

This is my input:

{
  "inputs": {
    "text": "Can you explain this sentence?  The United States also impinges on the global economy as a source of and as a destination for investment capital."
  },
  "options": {
    "wait_for_model": true,
    "use_cache": true
  },
  "parameters": {
    "min_length": 13,
    "top_k": 3,
    "temperature": 0,
    "max_time": 30,
    "max_length": 500
  }
}

I followed the docs. I don't know why it's not working.

breisa

May 10, 2024

•

edited May 10, 2024

Looked through the forums and seems like they changed the api without updating the docs. We should be looking at the text generation task docs instead.

The input should look something like this:

{
  "inputs": "Can you explain this sentence? The United States also impinges on the global economy as a source of and as a destination for investment capital.",
  "options": {
    "wait_for_model": true,
    "use_cache": true
  },
  "parameters": {
    "min_length": 12,
    "top_k": 3,
    "temperature": 0,
    "max_time": 30,
    "max_length": 500
  }
}

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