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_16-13-18_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764688398.tsf-508-wpa-2-088.epfl.ch.7997.0
- Xet hash:
- 5d22c03f58bbeb6112ff73976f7d12054a052e5b3d8f3e7c98af7e4bd530e701
- Size of remote file:
- 22.2 kB
- SHA256:
- 8d13b01a061f1229868541bbaf0b93294df6d58958d59fac6ea9470599d55731
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