Instructions to use dima806/toxic-comments-classifier-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/toxic-comments-classifier-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dima806/toxic-comments-classifier-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dima806/toxic-comments-classifier-distilbert") model = AutoModelForSequenceClassification.from_pretrained("dima806/toxic-comments-classifier-distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8142835e9d0a436a971dbaa6f0680c27243cc0f4172d874419b16ff4b2fb094
- Size of remote file:
- 438 MB
- SHA256:
- f1e018079ed3cdb87576aaf6ea532d30b3c61b2b28ad25547d008bc90efd930f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.