Instructions to use Dabid/test3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dabid/test3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Dabid/test3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Dabid/test3") model = AutoModelForSequenceClassification.from_pretrained("Dabid/test3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ae79f556d8cab640fb6c4af8a701cc9a90eb5ae606337d673321989d0db7c06
- Size of remote file:
- 3.45 kB
- SHA256:
- 0a9dd33d3204d2890955a311405589fd4d05b1014171d789c8eae50c6e4a9383
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