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 /Nov24_16-04-15_tsf-508-wpa-2-170.epfl.ch /events.out.tfevents.1763996704.tsf-508-wpa-2-170.epfl.ch.5947.0
- Xet hash:
- 23c86863dae05d96ba1ca140e790d37141d7d5c98a9c07af8e103419b6a6f80d
- Size of remote file:
- 12.4 kB
- SHA256:
- 70a38c8bf9d27c5b02de0c5fafddcfd86c8727d57b115a89f1df559ca0cd304b
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