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 /Nov30_14-33-01_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764509589.tsf-508-wpa-6-167.epfl.ch.7187.0
- Xet hash:
- cf59f68c7d1b2f40b2459f9ca68dc4426fcaba83e55ed55de631c79c4d47a026
- Size of remote file:
- 13.6 kB
- SHA256:
- c6f97ee78c3380240a88787a2e0c6928f3ca382cd2c36f6ee04b90373f7b9a11
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