Instructions to use aequa-tech/irony-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aequa-tech/irony-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aequa-tech/irony-it")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aequa-tech/irony-it") model = AutoModelForSequenceClassification.from_pretrained("aequa-tech/irony-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cf69a3b37ef424ca4b03018f568f999a643902c189a4aa6fce467b5bcca3531
- Size of remote file:
- 4.34 kB
- SHA256:
- ca7f97a46664ee73521d43d504c0c1bcc12ac14f848a407eace8b5ba5f98cb19
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.