Text Classification
Transformers
PyTorch
JAX
Safetensors
English
distilbert
text-embeddings-inference
Instructions to use hidude562/Wiki-Complexity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hidude562/Wiki-Complexity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hidude562/Wiki-Complexity")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hidude562/Wiki-Complexity") model = AutoModelForSequenceClassification.from_pretrained("hidude562/Wiki-Complexity") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80bb81296c54de3d68936a814a37e0c9d94055fe8e694c64acfb119ff0b86077
- Size of remote file:
- 268 MB
- SHA256:
- 89ebe8ca02e7c5757ba64e2cdd4d2566f0f56c7f55a39299b12470c07ba0c360
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