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:
- 5e17d8e3bc24305673988dd0490dbb2fd9e62553ef2bf4d720cf546d015a38c2
- Size of remote file:
- 9.21 kB
- SHA256:
- 382c467ece4f5a5610b00d206c173f1e34a48e7843bfca5eb9652c1c422e88f6
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