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_11-07-29_tsf-508-wpa-1-223.epfl.ch /events.out.tfevents.1764065284.tsf-508-wpa-1-223.epfl.ch.5865.0
- Xet hash:
- 5b24ed1cd7832a2fd68371bb82deeb980f9a5cb4514248a90dc587b3d1cc0849
- Size of remote file:
- 7.07 kB
- SHA256:
- 4ebc76661e7cf2e9fd835bc43bde40514e027f57df2c0b329be0a4a91c7e0556
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