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 /Nov19_14-48-14_tsf-508-wpa-6-122.epfl.ch /events.out.tfevents.1763560095.tsf-508-wpa-6-122.epfl.ch.6487.0
- Xet hash:
- 7b1fb057401a2b5919d8d7590705a1f7c6afc3df3f12cb94c0d90db29a0a5cc3
- Size of remote file:
- 7.93 kB
- SHA256:
- 1f5ba619c630482ebdf6c7f0d5ab36aadb376dd3fe47004e7c4d1931dbb93066
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