Instructions to use Sin/DialoGPT-small-zai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sin/DialoGPT-small-zai with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Sin/DialoGPT-small-zai")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Sin/DialoGPT-small-zai") model = AutoModelForCausalLM.from_pretrained("Sin/DialoGPT-small-zai") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Sin/DialoGPT-small-zai with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Sin/DialoGPT-small-zai" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Sin/DialoGPT-small-zai", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Sin/DialoGPT-small-zai
- SGLang
How to use Sin/DialoGPT-small-zai 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 "Sin/DialoGPT-small-zai" \ --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": "Sin/DialoGPT-small-zai", "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 "Sin/DialoGPT-small-zai" \ --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": "Sin/DialoGPT-small-zai", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Sin/DialoGPT-small-zai with Docker Model Runner:
docker model run hf.co/Sin/DialoGPT-small-zai
| /* | |
| * To change this license header, choose License Headers in Project Properties. | |
| * To change this template file, choose Tools | Templates | |
| * and open the template in the editor. | |
| */ | |
| package testbufferedreader; | |
| import java.io.*; | |
| /** | |
| * | |
| * @author etudiant | |
| */ | |
| public class TestBufferedReader { | |
| protected String source; | |
| public TestBufferedReader(String source) | |
| { | |
| this.source = source; | |
| lecture(); | |
| } | |
| /** | |
| * @param args the command line arguments | |
| */ | |
| public static void main(String[] args) { | |
| // TODO code application logic here | |
| new TestBufferedReader("source.txt"); | |
| } | |
| private void lecture() | |
| { | |
| try { | |
| String ligne; | |
| BufferedReader fichier = new BufferedReader(new FileReader(source)); | |
| while ((ligne = fichier.readLine())!= null) | |
| { | |
| System.out.println(ligne); | |
| } | |
| fichier.close(); | |
| } | |
| catch (Exception e) | |
| { | |
| e.printStackTrace(); | |
| } | |
| } | |
| } | |