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_14-25-03_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764509156.tsf-508-wpa-6-167.epfl.ch.6811.1
- Xet hash:
- 8f1230446906b15b60c772ce0249c22405fe67fe0681f69ae2b3f7bc3f06a11f
- Size of remote file:
- 12.5 kB
- SHA256:
- 3db763043175ae0c73f64ba02f94edbe67b5191a4acec449be98c39f38bc66aa
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