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_16-36-45_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764689806.tsf-508-wpa-2-088.epfl.ch.7997.3
- Xet hash:
- 193eabf28148eb1c182f8019125f3700bd5c70b52951e16325e1512fde9367bf
- Size of remote file:
- 19.7 kB
- SHA256:
- 0d6c97b696003db8f4c4982d7d6b7bddd4d46dc65dad2525ca868a0788b69a70
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