Text Classification
Transformers
PyTorch
Dutch
bert
text classification
sentiment analysis
domain adaptation
text-embeddings-inference
Instructions to use clips/republic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clips/republic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clips/republic")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clips/republic") model = AutoModelForSequenceClassification.from_pretrained("clips/republic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 683e958843d8dc6eb15336e8fa2ee52763b74aba45ef5458a2dba9494972f03c
- Size of remote file:
- 437 MB
- SHA256:
- f12cdccce71f582010baeb5dcf70d841f7768b2ff34b464c6a65fb2c8f950e23
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