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*This model was released on 2019-11-01 and added to Hugging Face Transformers on 2020-11-16.*

# DialoGPT

[DialoGPT](https://huggingface.co/papers/1911.00536) is trained on 147M conversation-like exchanges from Reddit. It achieves human-like performance in single-turn dialogue settings, generating relevant, contentful, and context-consistent responses. The pre-trained model and training pipeline are publicly available for research and development in neural response generation and intelligent open-domain dialogue systems.

<hfoptions id="usage">
<hfoption id="Pipeline">

```py
import torch
from transformers import pipeline

pipeline = pipeline(task="text-generation", model="microsoft/DialoGPT-medium", dtype="auto")
pipeline("Plants create energy through a process known as photosynthesis.")
```

</hfoption>
<hfoption id="AutoModel">

```py
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium", dtype="auto")
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")

inputs = tokenizer("Plants create energy through a process known as photosynthesis.", return_tensors="pt")
outputs = model.generate(**inputs, max_length=50)
print(tokenizer.decode(outputs[0]))
```

</hfoption>
</hfoptions>

## Usage tips

- Pad inputs on the right. DialoGPT uses absolute position embeddings.