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_08-31-36_tsf-508-wpa-1-223.epfl.ch /events.out.tfevents.1764055897.tsf-508-wpa-1-223.epfl.ch.1716.0
- Xet hash:
- 8afc086b1ffc749ad5a9a7209e2947005c81eba37b396e24e1acd54d65f8592f
- Size of remote file:
- 6.39 kB
- SHA256:
- eb3e0fb8ee220e54bcaa1cac867a01eb3d6a387394a19a18eca0f87edbab2885
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