Instructions to use ankitkupadhyay/xnlitest_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ankitkupadhyay/xnlitest_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ankitkupadhyay/xnlitest_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ankitkupadhyay/xnlitest_model") model = AutoModelForSequenceClassification.from_pretrained("ankitkupadhyay/xnlitest_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98f5a64b854efb4aa0335f2d0a605e8c16000df3fd573159b9b32dabbddf78f9
- Size of remote file:
- 1.11 GB
- SHA256:
- da7f7dfb78ebbcfb9d02620404b539beb6674394f22f2485474d19271ea11606
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