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 /Nov25_11-39-59_tsf-508-wpa-1-223.epfl.ch /events.out.tfevents.1764067200.tsf-508-wpa-1-223.epfl.ch.7107.0
- Xet hash:
- 884587d4f5b468e0cedb5ff6ed81b05bc15d980a869fe22c08445006779cc69c
- Size of remote file:
- 7.07 kB
- SHA256:
- 282267facf71288b2eefc9dd6af73d26474bf31dad7442aba95ca7cc7ae3e527
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