Instructions to use remiai3/Chatbot_by_microsoft_DialoGPT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use remiai3/Chatbot_by_microsoft_DialoGPT-small with Transformers:

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

pipe = pipeline("text-generation", model="remiai3/Chatbot_by_microsoft_DialoGPT-small")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("remiai3/Chatbot_by_microsoft_DialoGPT-small", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use remiai3/Chatbot_by_microsoft_DialoGPT-small with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "remiai3/Chatbot_by_microsoft_DialoGPT-small"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "remiai3/Chatbot_by_microsoft_DialoGPT-small",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/remiai3/Chatbot_by_microsoft_DialoGPT-small

SGLang

How to use remiai3/Chatbot_by_microsoft_DialoGPT-small 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 "remiai3/Chatbot_by_microsoft_DialoGPT-small" \
    --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": "remiai3/Chatbot_by_microsoft_DialoGPT-small",
		"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 "remiai3/Chatbot_by_microsoft_DialoGPT-small" \
        --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": "remiai3/Chatbot_by_microsoft_DialoGPT-small",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use remiai3/Chatbot_by_microsoft_DialoGPT-small with Docker Model Runner:
```
docker model run hf.co/remiai3/Chatbot_by_microsoft_DialoGPT-small
```

Simple Chatbot (CPU/GPU)

Model: microsoft/DialoGPT-small (MIT)
Task: Single-session conversational demo (no memory persistence).
Note: Here we just provide the resources for to run this models in the laptops we didn't develop this entire models we just use the open source models for the experiment this model is developed by Microsoft

Quick start (any project)

# 1) Create env
python -m venv venv && source .venv/bin/activate  # Windows: ./venv/Scripts/activate

# 2) Install deps
pip install -r requirements.txt

# 3) Run
python main.py --help

Tip: If you have a GPU + CUDA, PyTorch will auto-use it. If not, everything runs on CPU (slower but works).

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microsoft/DialoGPT-small

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