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:
- 13b6942f0e204d973ee5a22fa9f42bef29767a03964b96ca728c4f2b18362fae
- Size of remote file:
- 3.31 kB
- SHA256:
- c12d68cd872888978a20469b5d9e951994105f20963ff55aa4936fa206764ddb
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