Instructions to use serhanciftlikci/improved_adversarial_nli_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use serhanciftlikci/improved_adversarial_nli_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="serhanciftlikci/improved_adversarial_nli_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("serhanciftlikci/improved_adversarial_nli_model") model = AutoModelForSequenceClassification.from_pretrained("serhanciftlikci/improved_adversarial_nli_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from serhanciftlikci/improved_adversarial_nli_model: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/serhanciftlikci/improved_adversarial_nli_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://serhanciftlikci/improved_adversarial_nli_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/serhanciftlikci/improved_adversarial_nli_model/resolve/main/pytorch_model.bin
738 MB
- Xet hash:
- 932211c1be502d8a0e7d0697958398131f63d6a687d098b18755b39f22823897
- Size of remote file:
- 738 MB
- SHA256:
- e56431d9ad8c23a0de44461822c388661ef8cebe5912d0313f561e4e31baa0b8
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