Instructions to use hadjebi/finetuned-deepset-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hadjebi/finetuned-deepset-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hadjebi/finetuned-deepset-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hadjebi/finetuned-deepset-model") model = AutoModelForSequenceClassification.from_pretrained("hadjebi/finetuned-deepset-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33f712887adc86bd4ae0e44a9d3751e36df37ac1e1c5624c3aa50b5d98a54098
- Size of remote file:
- 774 MB
- SHA256:
- df0fc3088047f47bd9a9c56256c98c27bf8ada9d991e080c22109ffd5f7dbed6
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