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 /Dec04_18-04-05_tsf-508-wpa-0-031.epfl.ch /events.out.tfevents.1764867846.tsf-508-wpa-0-031.epfl.ch.1760.0
- Xet hash:
- e672aad1632eea741e5a7cb8296d8b7f432fbe087fa0729aab95ae45600edefd
- Size of remote file:
- 5.43 kB
- SHA256:
- 2c7006edd0874465829313b386cadffd2760b2f3d8904d565535f3815a3f70cb
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