Instructions to use Atif-Memon/tRAINING-DATASET-All-files-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atif-Memon/tRAINING-DATASET-All-files-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Atif-Memon/tRAINING-DATASET-All-files-final")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Atif-Memon/tRAINING-DATASET-All-files-final") model = AutoModelForSequenceClassification.from_pretrained("Atif-Memon/tRAINING-DATASET-All-files-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 032d30fb13ad1a26eeee18bad789e11cea49a54f6efa08ff21b0ea0da1384f9a
- Size of remote file:
- 268 MB
- SHA256:
- 812b8cb689a5dbbe19f982a3274eec6d010ff1bf4eb316d6b017d00d9bcb8097
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