Instructions to use gowitheflow/p9-iter3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gowitheflow/p9-iter3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gowitheflow/p9-iter3")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("gowitheflow/p9-iter3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b406b4eb5dc82d647fa37371511243a071f7fe18933469181dadb69ada98b46e
- Size of remote file:
- 3.18 kB
- SHA256:
- 8a3819c49352298be9c93a53aa22a51dcb1078d6e39a93e96a3cb9c6d9979fd6
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