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.1764603087.tsf-508-wpa-6-167.epfl.ch.2144.2
- Xet hash:
- 0fde98103a3b593d6c6fb4d0e0b2a3026cdc66c470de0cc47664d29d45a037aa
- Size of remote file:
- 411 Bytes
- SHA256:
- 7880ba36bb61cc2e2b3eceb95f34471375829adf7fc9f17c2ef13531d0151f54
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