How to use microsoft/DialoGPT-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="microsoft/DialoGPT-small") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-small") model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-small") 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]:]))
How to use microsoft/DialoGPT-small with vLLM:
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "microsoft/DialoGPT-small" # 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-small", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'
docker model run hf.co/microsoft/DialoGPT-small
How to use microsoft/DialoGPT-small with SGLang:
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "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/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "microsoft/DialoGPT-small", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'
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-small" \ --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-small", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'
How to use microsoft/DialoGPT-small with Docker Model Runner:
Is it possible to fine tune this model on our own data?
yes, maybe, all you need to know the special tokens which is used
Can it be trained ONLY on CPU? (0-0 )
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