Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use HAOUHAT/legal-doctrine-Coding-Challenge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HAOUHAT/legal-doctrine-Coding-Challenge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HAOUHAT/legal-doctrine-Coding-Challenge")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HAOUHAT/legal-doctrine-Coding-Challenge") model = AutoModelForSequenceClassification.from_pretrained("HAOUHAT/legal-doctrine-Coding-Challenge") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 315a609635c26852b8f742955c9e12bd2991fdb566fbe5875caa2221dbec2c32
- Size of remote file:
- 3.58 kB
- SHA256:
- 202642fd90cb41ca5a096d80237f331d65844c4ad1662a9de09ac80e6ccece67
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