Instructions to use arnav7633/DialoGPT-medium-tony_stark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use arnav7633/DialoGPT-medium-tony_stark with Transformers:

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

pipe = pipeline("text-generation", model="arnav7633/DialoGPT-medium-tony_stark")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("arnav7633/DialoGPT-medium-tony_stark")
model = AutoModelForCausalLM.from_pretrained("arnav7633/DialoGPT-medium-tony_stark")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use arnav7633/DialoGPT-medium-tony_stark with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "arnav7633/DialoGPT-medium-tony_stark"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "arnav7633/DialoGPT-medium-tony_stark",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/arnav7633/DialoGPT-medium-tony_stark

SGLang

How to use arnav7633/DialoGPT-medium-tony_stark 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 "arnav7633/DialoGPT-medium-tony_stark" \
    --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": "arnav7633/DialoGPT-medium-tony_stark",
		"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 "arnav7633/DialoGPT-medium-tony_stark" \
        --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": "arnav7633/DialoGPT-medium-tony_stark",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use arnav7633/DialoGPT-medium-tony_stark with Docker Model Runner:
```
docker model run hf.co/arnav7633/DialoGPT-medium-tony_stark
```

YAML Metadata Error:"license" must be one of [apache-2.0, mit, openrail, bigscience-openrail-m, creativeml-openrail-m, bigscience-bloom-rail-1.0, bigcode-openrail-m, afl-3.0, artistic-2.0, bsl-1.0, bsd, bsd-2-clause, bsd-3-clause, bsd-3-clause-clear, c-uda, cc, cc0-1.0, cc-by-2.0, cc-by-2.5, cc-by-3.0, cc-by-4.0, cc-by-sa-3.0, cc-by-sa-4.0, cc-by-nc-2.0, cc-by-nc-3.0, cc-by-nc-4.0, cc-by-nd-4.0, cc-by-nc-nd-3.0, cc-by-nc-nd-4.0, cc-by-nc-sa-2.0, cc-by-nc-sa-3.0, cc-by-nc-sa-4.0, cdla-sharing-1.0, cdla-permissive-1.0, cdla-permissive-2.0, wtfpl, ecl-2.0, epl-1.0, epl-2.0, etalab-2.0, eupl-1.1, eupl-1.2, agpl-3.0, gfdl, gpl, gpl-2.0, gpl-3.0, lgpl, lgpl-2.1, lgpl-3.0, isc, h-research, intel-research, lppl-1.3c, ms-pl, apple-ascl, apple-amlr, mpl-2.0, odc-by, odbl, open-mdw, openrail++, osl-3.0, postgresql, ofl-1.1, ncsa, unlicense, zlib, pddl, lgpl-lr, deepfloyd-if-license, fair-noncommercial-research-license, llama2, llama3, llama3.1, llama3.2, llama3.3, llama4, gemma, unknown, other, array]

A casual chatbot

This is a dialogpt medium fine tuned to talk like Tony Stark, Currently its only trained upon the script of Iron man 3

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