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 /Nov25_08-36-44_tsf-508-wpa-1-223.epfl.ch /events.out.tfevents.1764056204.tsf-508-wpa-1-223.epfl.ch.1964.0
- Xet hash:
- 5ff35258e9c58b6d852d4b6d59f539340a3c701bb39a2262ca5985f889d583cd
- Size of remote file:
- 7.93 kB
- SHA256:
- c6807974ee14d16fd8140273ccb96ca9895fdccd6452f40523a8b8f5f5d78396
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