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 /Dec03_17-25-55_tsf-508-wpa-0-192.epfl.ch /events.out.tfevents.1764779157.tsf-508-wpa-0-192.epfl.ch.4713.1
- Xet hash:
- f5eda635c46fd448ef2a652df013e71b5f0a5fe11365b0a51d9b6a27a6504462
- Size of remote file:
- 23.3 kB
- SHA256:
- 47e8b186b8fd85449a3d65ad23f2dad32bb7f6a41630c4e38e304aeb17c98db7
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