Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use NurErtug/crowd_sourced_web_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NurErtug/crowd_sourced_web_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NurErtug/crowd_sourced_web_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NurErtug/crowd_sourced_web_classifier") model = AutoModelForSequenceClassification.from_pretrained("NurErtug/crowd_sourced_web_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
crowd_sourced_web_classifier / runs /Dec01_10-39-50_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764581991.tsf-508-wpa-6-167.epfl.ch.3602.1
- Xet hash:
- ae8f1e479870135c84051cac97f872777a1afbf92bc197d520f4d87be89a8599
- Size of remote file:
- 17.4 kB
- SHA256:
- ee56649691f5067bece25657c7a585286e4f3b66d115f692a78a62e508301ed8
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