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 /Dec02_11-24-15_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764671056.tsf-508-wpa-2-088.epfl.ch.2839.0
- Xet hash:
- 1ed413fe09c3949f3f7c9f68439ae4c11df70d7940250ef027fc4ee848d26619
- Size of remote file:
- 19.6 kB
- SHA256:
- 59255c73b68ac5b60dc1d93822a6a5e31e094621b7216f282deec2809f078aa0
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