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_16-33-49_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764689630.tsf-508-wpa-2-088.epfl.ch.7997.2
- Xet hash:
- 1a6dfc9836138ce8fe8fec102bece07d34038f25ff1f5e47f9b1f7566af94518
- Size of remote file:
- 19.7 kB
- SHA256:
- 1ef21d13cbebf8c6b1518ffb88beab40ff8fa9d36adf434debac549143ed0d89
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