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 /Nov19_15-10-57_tsf-508-wpa-6-122.epfl.ch /events.out.tfevents.1763561458.tsf-508-wpa-6-122.epfl.ch.6487.2
- Xet hash:
- dd13b814967d77a610f43a4b214ee56171f2d4f1180203ca1a3cf1a52fa7ee0d
- Size of remote file:
- 5.43 kB
- SHA256:
- 75645ac1938de9dafa858248f004b19d817748c137dce432176448d231fb1ec9
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