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:
- 8a6047d3ab9b0deea425dcb32f39d4b34ac8c8f5de6e520c4b09ef62d890aa26
- Size of remote file:
- 268 MB
- SHA256:
- 3455773174ea208af20469fb2135994f904f7f41820d1f9bfb30ed9f4a5e2960
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