Instructions to use rorschach-40/home-batch_3_2000_-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rorschach-40/home-batch_3_2000_-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rorschach-40/home-batch_3_2000_-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rorschach-40/home-batch_3_2000_-text-classification") model = AutoModelForSequenceClassification.from_pretrained("rorschach-40/home-batch_3_2000_-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33e47af3241a904c4b86d1e58ad6fde056c5bd5684df6c680da8cadb3501efdb
- Size of remote file:
- 4.79 kB
- SHA256:
- f06c154b3264571a108df2c0fab94bc0f0a5973c968bb7644dc46866f1e5b0a9
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