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_13-03-31_tsf-508-wpa-1-223.epfl.ch /events.out.tfevents.1764072213.tsf-508-wpa-1-223.epfl.ch.7606.0
- Xet hash:
- f154298b8dce2aa4e073d480f6068dbd7d190361c1b02941602de603468b4629
- Size of remote file:
- 7.07 kB
- SHA256:
- ef14d5110f99b83c1852a6ac1d800fb661963085e1996da0c4141a617d7e92c0
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