Instructions to use RabidUmarell/toxic-mbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RabidUmarell/toxic-mbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RabidUmarell/toxic-mbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RabidUmarell/toxic-mbert") model = AutoModelForSequenceClassification.from_pretrained("RabidUmarell/toxic-mbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e2c1458378257d29029ac6ad9d27f7a1478a365a329cd323d2c30b4e877c9dd
- Size of remote file:
- 4.73 kB
- SHA256:
- 13e1e98689fe171b8a0795459a7b21fd7f54caa699e8895365cb71eb31905978
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.