Instructions to use liamcripwell/ctrl44-clf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liamcripwell/ctrl44-clf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="liamcripwell/ctrl44-clf")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("liamcripwell/ctrl44-clf") model = AutoModelForSequenceClassification.from_pretrained("liamcripwell/ctrl44-clf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5fd28fd82e513d0b3956eed3df74917dfbf93730b266a8f01142f6d2f1e89b4
- Size of remote file:
- 499 MB
- SHA256:
- de57c8de1ed93b2e29b32c34680ebe96c562fa816c698275241ac78915ec589f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.