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_16-25-02_tsf-508-wpa-2-170.epfl.ch /events.out.tfevents.1763997903.tsf-508-wpa-2-170.epfl.ch.7101.1
- Xet hash:
- 12c0789c34b42c655a3284728fbd943bfa0a3045d5b4c74e79c521a623aa7fed
- Size of remote file:
- 6.93 kB
- SHA256:
- 16090382ac02112771f3436e11d586d6515bcf9fab50915658fe8eb84d98018b
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