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_17-25-24_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764606324.tsf-508-wpa-6-167.epfl.ch.3594.1
- Xet hash:
- b6cbb3a168394cc1513f8b154d2d16a054e25faa361840c616615c2749f0aff8
- Size of remote file:
- 19.6 kB
- SHA256:
- d09028de9f6375033e6b76234ed81a232bf86926391a03bba0c84d6abd7a0782
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