Text Classification
Transformers
PyTorch
distilbert
classification
Generated from Trainer
text-embeddings-inference
Instructions to use cedomin/Task1a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cedomin/Task1a with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cedomin/Task1a")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cedomin/Task1a") model = AutoModelForSequenceClassification.from_pretrained("cedomin/Task1a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f11a18d300e0cafb51d0ef5498152165e75674f3c8b14bc4527a92d4662bc8f
- Size of remote file:
- 3.52 kB
- SHA256:
- d1f40357252a64d4397a92448a61b46d5c9e6895d315d0eaf86eadadf17f6fea
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