Instructions to use id66pj/runs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use id66pj/runs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="id66pj/runs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("id66pj/runs") model = AutoModelForSequenceClassification.from_pretrained("id66pj/runs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d53027db772883c8d29371adf41c2ecfc61a5668a4d4c67f776dc6470aa44326
- Size of remote file:
- 5.2 kB
- SHA256:
- 3895a1ab6a94e617dfe21e1d875c53bfdcf6f8c5e9a995310abbd5aec0311f0a
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