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_10-44-03_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764582297.tsf-508-wpa-6-167.epfl.ch.3860.3
- Xet hash:
- 88faaf9aea71bca1a60b47ecdbac33847946682547e46c6dadd5a6e591e29be1
- Size of remote file:
- 411 Bytes
- SHA256:
- d9447b4e9ca20f582adfd1ed28ac29c6e7add077127c7ef14d83626813d79a33
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