Text Classification
Transformers
PyTorch
Dutch
bert
Generated from Trainer
text-embeddings-inference
Instructions to use denizspynk/requirements_ambiguity_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use denizspynk/requirements_ambiguity_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="denizspynk/requirements_ambiguity_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("denizspynk/requirements_ambiguity_v2") model = AutoModelForSequenceClassification.from_pretrained("denizspynk/requirements_ambiguity_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cdc72cd9a273e49fcffe76fe653d8253e5e03105aff1ba5f9cb57479be906a59
- Size of remote file:
- 3.39 kB
- SHA256:
- f52726f03e4b14592ff3d40677dd80f46b43f1aabdd9e27ea02d4c33ab03f1bf
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