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_14-37-53_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764509874.tsf-508-wpa-6-167.epfl.ch.7187.4
- Xet hash:
- b266646d54d4fda1d9a75e0cd39c5bbe21b91ca6a3425a8d9c493c843c6a4b61
- Size of remote file:
- 13.6 kB
- SHA256:
- 07d72c4ad717d864e956059b2ede640952121b684660e48c2cabbbe5427b6bb8
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