Instructions to use gowitheflowlab/en-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gowitheflowlab/en-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gowitheflowlab/en-it")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("gowitheflowlab/en-it", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9eea63d66603e9c1cab0a6a5fbb033452f4ea77d770d7fb9376a6170c408acd7
- Size of remote file:
- 3.38 kB
- SHA256:
- c3718fe60bc3ff039b9b07416fa4cab3029f1b56004e442fa07ae46a8de909ee
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.