Instructions to use hazem74/firstModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hazem74/firstModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hazem74/firstModel", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hazem74/firstModel") model = AutoModelForSequenceClassification.from_pretrained("hazem74/firstModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1de0441e233ad33894f7084a827a446c69b140cc1220528d7d0d0d3105fbd4d
- Size of remote file:
- 438 MB
- SHA256:
- f13bbffdaa00d2042dcd06b23e9807bdb605f92f55ffac8c07f3d13efd6a6d0a
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