---
license: apache-2.0
language:
- en
pipeline_tag: text2text-generation
---

Some example code to load our model locally and generate a prediction:
```
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Dede1989600/hatespeech_mCAD")
model = AutoModelForSeq2SeqLM.from_pretrained("Dede1989600/hatespeech_mCAD")

inputs = tokenizer("This is a test that should be labeled as no hate", return_tensors="pt")
outputs = model.generate(**inputs)
tokenizer.decode(outputs[0], skip_special_tokens=True)

```

The model returns either 1 for hatespeech or 0 for no hatespeech