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_13-17-43_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764677863.tsf-508-wpa-2-088.epfl.ch.4377.0
- Xet hash:
- 5be8574f5b897ddb64096d6354051484a9774887fbcdfa54816444590cef7488
- Size of remote file:
- 19.6 kB
- SHA256:
- 10b4af4b21bfd17aabafe87413301d9a3832ced60c617596c8c5fa983b499029
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