Instructions to use Mahmoud22/All-Train-data-F1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud22/All-Train-data-F1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mahmoud22/All-Train-data-F1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mahmoud22/All-Train-data-F1") model = AutoModelForSequenceClassification.from_pretrained("Mahmoud22/All-Train-data-F1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1133d9ad9dac2e7aa9817569cb10f181bbe211dca43c28f4214ff1b9bdde4314
- Size of remote file:
- 541 MB
- SHA256:
- 42a3b26b6eb0dc079d2b3bd63abcef3e767e9a1023a4f7230714ebb7a65f1115
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