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_15-03-33_tsf-508-wpa-6-122.epfl.ch /events.out.tfevents.1763561014.tsf-508-wpa-6-122.epfl.ch.6487.1
- Xet hash:
- 3a5172537977c79fe2d383742a2334be8071b3d12d22d3e9b4ab982d16083cd2
- Size of remote file:
- 6.39 kB
- SHA256:
- 51bd0a48edf7c95c0953fbf8edebdd6ea26f452b1b62bb1d1b3abe07885eede2
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