Instructions to use rorschach-40/home-window_5000_batch_9-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rorschach-40/home-window_5000_batch_9-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rorschach-40/home-window_5000_batch_9-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rorschach-40/home-window_5000_batch_9-classification") model = AutoModelForSequenceClassification.from_pretrained("rorschach-40/home-window_5000_batch_9-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3df74280cba916d708c738474cc92d79287a469f43134d5169a69dfa63ed76e
- Size of remote file:
- 4.79 kB
- SHA256:
- 9f3b2fc39b15395408c36d8fb9a4ef5a0e8712fb43b294186cdbe167df6a1f92
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