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:
- 41682aa175db84d8cb115eb1dd7e3b0f6b9d2ef6931b0d1eada20edeea457c1d
- Size of remote file:
- 3.45 kB
- SHA256:
- c793fb12e384f055712929c17cab70c0be84d2207067abc0f6ce08f74fc26b6c
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