transformers pytorch phi text-generation autotrain_compatible endpoints_compatible text-generation-inference region:us
Copied from https://huggingface.co/susnato/phi-2 commit@9070ddb4fce238899ddbd2aca1faf6a0aeb6e444.

This model can be loaded using HuggingFace `transformers` [commit@4ab5fb8941a38d172b3883c152c34ae2a0b83a68](https://github.com/huggingface/transformers/tree/4ab5fb8941a38d172b3883c152c34ae2a0b83a68).

Below is the original introduction, which may be expired now.






----------------------------------------------------



**DISCLAIMER**: I don't own the weights to this model, this is a property of Microsoft and taken from their official repository : [microsoft/phi-2](https://huggingface.co/microsoft/phi-2).
The sole purpose of this repository is to use this model through the `transformers` API or to load and use the model using the HuggingFace `transformers` library.


# Usage 

First make sure you have the latest version of the `transformers` installed.

```
pip install -U transformers
```

Then use the transformers library to load the model from the library itself

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("susnato/phi-2")
tokenizer = AutoTokenizer.from_pretrained("susnato/phi-2")

inputs = tokenizer('''def print_prime(n):
   """
   Print all primes between 1 and n
   """''', return_tensors="pt", return_attention_mask=False)

outputs = model.generate(**inputs, max_length=200)
text = tokenizer.batch_decode(outputs)[0]
print(text)

```