Instructions to use DimasikKurd/rubert-base-cased_neg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DimasikKurd/rubert-base-cased_neg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DimasikKurd/rubert-base-cased_neg")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DimasikKurd/rubert-base-cased_neg") model = AutoModelForTokenClassification.from_pretrained("DimasikKurd/rubert-base-cased_neg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01c153abd5636554fb18c418d22d6c64d736bdbf01b8b629fbc1fdb45c7de320
- Size of remote file:
- 4.92 kB
- SHA256:
- 951f10d1ca867d8ffc99b4826e602bdbd5dfff86b82e3f9d2bd7b0190ca28f23
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