Instructions to use Ashishkr/query_wellformedness_score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ashishkr/query_wellformedness_score with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ashishkr/query_wellformedness_score")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ashishkr/query_wellformedness_score") model = AutoModelForSequenceClassification.from_pretrained("Ashishkr/query_wellformedness_score") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8726d8167e61f3383c21929ec272458dec798ef9650eb62feb4838676055f2f6
- Size of remote file:
- 501 MB
- SHA256:
- 1b44872b943930c055f1f7e24871cd835b72aeaed6ac25e97e8ce4eb3a545b44
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.