Instructions to use NaNOrange/my_first_uploaded_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NaNOrange/my_first_uploaded_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NaNOrange/my_first_uploaded_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NaNOrange/my_first_uploaded_model") model = AutoModelForSequenceClassification.from_pretrained("NaNOrange/my_first_uploaded_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7b932d59f6bd8f51d88a9d41beda1629b1aba582edc2abeca0d30c5bf8ad169
- Size of remote file:
- 5.3 kB
- SHA256:
- 4b1f27942b53826c37178de9af01c9e37a421e1952d4f42ed511be7c1405be8e
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