Instructions to use cmcmorrow/distilbert-rater with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cmcmorrow/distilbert-rater with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cmcmorrow/distilbert-rater")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cmcmorrow/distilbert-rater") model = AutoModelForSequenceClassification.from_pretrained("cmcmorrow/distilbert-rater", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94dd2e4e92967729fc9e93b5e5b90fc8febfd79c48b954eca67d4d3a641c0966
- Size of remote file:
- 3.06 kB
- SHA256:
- 63d5423ea4cb92454043777b2b87742f80b6e4953058f2557709200c64e0903e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.