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 /Nov24_15-31-58_tsf-508-wpa-2-170.epfl.ch /events.out.tfevents.1763994719.tsf-508-wpa-2-170.epfl.ch.5419.0
- Xet hash:
- a70e1f356abad865dca195a669f8be01beaa1e79d46cbf881e210829742cb71d
- Size of remote file:
- 6.93 kB
- SHA256:
- d1c682d9e69b6492fe58f4f333a37e76ba319e0f8c5fd204c6833fb834a731d3
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