Instructions to use MagmaCubes1133/DialoGPT-large-rick with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MagmaCubes1133/DialoGPT-large-rick with Transformers:

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

pipe = pipeline("text-generation", model="MagmaCubes1133/DialoGPT-large-rick")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MagmaCubes1133/DialoGPT-large-rick")
model = AutoModelForCausalLM.from_pretrained("MagmaCubes1133/DialoGPT-large-rick")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use MagmaCubes1133/DialoGPT-large-rick with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MagmaCubes1133/DialoGPT-large-rick"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MagmaCubes1133/DialoGPT-large-rick",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/MagmaCubes1133/DialoGPT-large-rick

SGLang

How to use MagmaCubes1133/DialoGPT-large-rick 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 "MagmaCubes1133/DialoGPT-large-rick" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MagmaCubes1133/DialoGPT-large-rick",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "MagmaCubes1133/DialoGPT-large-rick" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MagmaCubes1133/DialoGPT-large-rick",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use MagmaCubes1133/DialoGPT-large-rick with Docker Model Runner:
```
docker model run hf.co/MagmaCubes1133/DialoGPT-large-rick
```

DialoGPT-large-rick

Commit History

Adding `safetensors` variant of this model (#1)

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MagmaCubes1133

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Initial Commit

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initial commit

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Commit History

Adding `safetensors` variant of this model (#1) 8c5e157 verified

Create README.md b0c6dfd

Initial Commit 6415146

Delete eval_results.txt e8f7e97

Delete config.json 8e123d1

Delete merges.txt 6d0faf9

Initial Commit b492a78

Upload merges.txt c986eab

Upload eval_results.txt 0e84e35

Upload config.json 026c7a0

initial commit 4e1f226

Adding `safetensors` variant of this model (#1)

8c5e157
verified

Create README.md

b0c6dfd

Initial Commit

6415146

Delete eval_results.txt

e8f7e97

Delete config.json

8e123d1

Delete merges.txt

6d0faf9

Initial Commit

b492a78

Upload merges.txt

c986eab

Upload eval_results.txt

0e84e35

Upload config.json

026c7a0

initial commit

4e1f226