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*This model was released on 2020-12-01 and added to Hugging Face Transformers on 2021-04-10 and contributed by [canwenxu](https://huggingface.co/canwenxu).*

# CPM

[CPM: A Large-scale Generative Chinese Pre-trained Language Model](https://huggingface.co/papers/2012.00413) is the largest Chinese pre-trained language model with 2.6 billion parameters and 100GB of Chinese training data. It facilitates various downstream NLP tasks including conversation, essay generation, cloze test, and language understanding. Extensive experiments show that CPM performs strongly in few-shot and zero-shot learning settings. Its architecture mirrors GPT-2, with the primary difference being the tokenization method.

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

```py
import torch
from transformers import pipeline

pipeline = pipeline(task="text-generation", model="TsinghuaAI/CPM-Generate", dtype="auto")
pipeline("植物通过光合作用产生能量。")
```

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

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

model = AutoModelForCausalLM.from_pretrained("TsinghuaAI/CPM-Generate", dtype="auto")
tokenizer = AutoTokenizer.from_pretrained("TsinghuaAI/CPM-Generate")

inputs = tokenizer("植物通过光合作用产生能量。", return_tensors="pt")
outputs = model.generate(**inputs, max_length=50, do_sample=True)
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(generated_text)
```

</hfoption>
</hfoptions>

## CpmTokenizer

[[autodoc]] CpmTokenizer

## CpmTokenizerFast

[[autodoc]] CpmTokenizerFast

