Instructions to use tvaldez/classifier-chapter6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tvaldez/classifier-chapter6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tvaldez/classifier-chapter6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tvaldez/classifier-chapter6") model = AutoModelForSequenceClassification.from_pretrained("tvaldez/classifier-chapter6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f765f68d6d1dcc5500a10f276dafe771e7ac4b7b38a5d073ddb10c2d4caca99
- Size of remote file:
- 5.84 kB
- SHA256:
- 6a54f690a230ba1d9faa144555db0181b2a375e82a912cb1bd5467ce2721ed98
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