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 /Nov25_10-57-45_tsf-508-wpa-1-223.epfl.ch /events.out.tfevents.1764064666.tsf-508-wpa-1-223.epfl.ch.5344.0
- Xet hash:
- a10fd30b87513dcc7b35e0b7d936dd8138c46d7f15036586f2d95773b85d3a61
- Size of remote file:
- 7.07 kB
- SHA256:
- 8e5659d2db4473da6a488dbd148718dca0799b8dcaf1deb4ddf6881aaef91fd1
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