File size: 1,430 Bytes
e101b09 a270fba 35932b3 e101b09 4f1bd07 e101b09 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | 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)
``` |