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 /Dec01_09-49-22_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764578964.tsf-508-wpa-6-167.epfl.ch.2424.0
- Xet hash:
- 617bfe7491427a8d21f6e6159121c3e2569a25dd3c6b3329c298f60db21caaad
- Size of remote file:
- 14.4 kB
- SHA256:
- 17e1dc5d8b088e139da3dba3e88e4b4089d672c2f202dddc46371253f65cbb3b
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