Instructions to use aloxatel/9WT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aloxatel/9WT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aloxatel/9WT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aloxatel/9WT") model = AutoModelForSequenceClassification.from_pretrained("aloxatel/9WT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42d8a81f9c16148263ee17a204b0d52ed5f42b26630cc4262adb319624c86517
- Size of remote file:
- 669 MB
- SHA256:
- a34a38257d41f2eeb20b433ce7325bf751b7c355ce4773710f821f346e5249a0
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