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 /Dec01_10-38-51_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764582043.tsf-508-wpa-6-167.epfl.ch.3602.2
- Xet hash:
- 016b1bb05682e279078d9c766a7ca5e05c1c92ad64233775dd2e8bd300c03bca
- Size of remote file:
- 411 Bytes
- SHA256:
- e8b908422747cd55a0c04344c2daedf6fd51509efe2ac4597cde4b4deeb87731
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