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
```

This thing is racist as hell

by deleted - opened Apr 30, 2023

Discussion

deleted

Apr 30, 2023

PLEASE fix this, it's doing this every time. And I know, it's AI, but this gotta be fixed

nikich340

May 16, 2023

Lol. If you don't like any of responses, just don't use the model or filter out unwanted responses.
P.S. No one owes you anything when it comes to using an open-source free model.

maxolotl

Jul 20, 2023

•

edited Jul 20, 2023

Yep this is a big issue, it gave me the exchange:

>> User: Are you racist?
DialoGPT: I'm not racist, but I am a racist.

zhangbo2008

Jul 28, 2023

oh my god. this thing is dizaster

vltmedia

Sep 12, 2023

What's up with the smooth brain comments in here?

eXorcyst

Mar 4, 2024

Y'all realize this model was pre-trained on data collected from Reddit, right?

datasciguy

Mar 6, 2024

•

edited Mar 6, 2024

It was trying to be funny, I think. Also, there's 2 different ways you could interpret its attempt at humor, one of which is genuinely funny:

1. It's attempting sarcastic humor by facetiously implying a dislike for others along racial lines 
          but due to non-race-specific dislike of heterogeneity (less likely, less funny / not funny).
2. It's attempting sarcastic humor by facetiously implying a dislike for others (not along racial lines) due to
          dislike of heterogeneity (more likely, funnier).

Also bear in mind, this is a second-tier model in an area of application where the best-in-class models still make giant dumb errors frequently.

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