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 /Dec02_10-25-50_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764667551.tsf-508-wpa-2-088.epfl.ch.1560.0
- Xet hash:
- ada8998c728e1683b6c811a2397e1677eb9231ad0aad80c07e0f10f3bf3d787f
- Size of remote file:
- 19.6 kB
- SHA256:
- 4ec246b39f6c40d9c35f01d5d4565c003de5462af4c914fafb49fe937e857cd3
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