Text Classification
Transformers
PyTorch
English
distilbert
classification
text-embeddings-inference
Instructions to use lingwave-admin/state-op-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lingwave-admin/state-op-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lingwave-admin/state-op-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lingwave-admin/state-op-detector") model = AutoModelForSequenceClassification.from_pretrained("lingwave-admin/state-op-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c26efd7e163906cbf4c731ae1ca264d139ca9c8814ab4215bf8c6e448ba25d30
- Size of remote file:
- 268 MB
- SHA256:
- 05ce03b6f1d72465e677b73a5cb0d001a82cbd62e080eead5a6c5632754c870b
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