Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ClaraPind/classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ClaraPind/classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ClaraPind/classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ClaraPind/classifier") model = AutoModelForSequenceClassification.from_pretrained("ClaraPind/classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db13fdc18631bdd91c5bc00e169b72084d1749422f5fd80464e89f89af56a744
- Size of remote file:
- 268 MB
- SHA256:
- ad6039f2370ca9b8c54ed4cebcba4eaa585c219e94c3e9204dc78e37d78710c0
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