| This model is based on a custom Transformer model that can be installed with: | |
| ```bash | |
| pip install git+https://github.com/lucadiliello/bleurt-pytorch.git | |
| ``` | |
| Now load the model and make predictions with: | |
| ```python | |
| import torch | |
| from bleurt_pytorch import BleurtConfig, BleurtForSequenceClassification, BleurtTokenizer | |
| config = BleurtConfig.from_pretrained('lucadiliello/bleurt-base-512') | |
| model = BleurtForSequenceClassification.from_pretrained('lucadiliello/bleurt-base-512') | |
| tokenizer = BleurtTokenizer.from_pretrained('lucadiliello/bleurt-base-512') | |
| references = ["a bird chirps by the window", "this is a random sentence"] | |
| candidates = ["a bird chirps by the window", "this looks like a random sentence"] | |
| model.eval() | |
| with torch.no_grad(): | |
| inputs = tokenizer(references, candidates, padding='longest', return_tensors='pt') | |
| res = model(**inputs).logits.flatten().tolist() | |
| print(res) | |
| # [1.1482683420181274, 0.7443546056747437] | |
| ``` | |
| Take a look at this [repository](https://github.com/lucadiliello/bleurt-pytorch) for the definition of `BleurtConfig`, `BleurtForSequenceClassification` and `BleurtTokenizer` in PyTorch. |