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 /Nov30_14-07-21_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764508043.tsf-508-wpa-6-167.epfl.ch.4660.2
- Xet hash:
- 503207cf83f6a474ea2e886b3a5f0eedd9344a0d4ec0f08751bc763cb0e3cd8e
- Size of remote file:
- 13.6 kB
- SHA256:
- e2d69a4b7a52df2b1443716f61f6f078e27f4a97de8aae2fbabdce482f90691d
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