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_16-29-55_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764602996.tsf-508-wpa-6-167.epfl.ch.2144.0
- Xet hash:
- d6fbdb534c9a09b2f5a140ece3a3dd1ec6de95f8321f27d58566d2b2698edfec
- Size of remote file:
- 13.6 kB
- SHA256:
- 041dbfb48634f815a541aa5e9ab323b1879380696a6269a0755a4f54cd198322
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