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 /Dec01_09-43-34_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764578615.tsf-508-wpa-6-167.epfl.ch.2181.1
- Xet hash:
- a8d9a872935c45bccb90f689d928aa31079acf9c331bff07342732afeaf0a43b
- Size of remote file:
- 13.6 kB
- SHA256:
- eeb79598a0fdbe09b3f6380ae8f223ed8f59fcddc20e4c435cc3cb9461927af8
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