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_14-37-20_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764682641.tsf-508-wpa-2-088.epfl.ch.6326.1
- Xet hash:
- 39277cb38c11bf3e4a709717811076dfab566051cd1a031b69bb8d1f9cbdd6d4
- Size of remote file:
- 18.8 kB
- SHA256:
- 77be5289a12a06f61e0bf24e7ba795aa42283f35a9aec83164d1895e2ee79f77
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