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_11-32-59_tsf-508-wpa-1-223.epfl.ch /events.out.tfevents.1764066781.tsf-508-wpa-1-223.epfl.ch.6855.0
- Xet hash:
- 20f1a855435778914f16880ce34ab277f28ae6383342acc14aec5963bb90db80
- Size of remote file:
- 5.43 kB
- SHA256:
- e41707154ed2984a0a6e3dcd91bbf629ace969c3724a83710e3dfbefa0ac03c1
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