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 /Dec03_17-08-24_tsf-508-wpa-0-192.epfl.ch /events.out.tfevents.1764778105.tsf-508-wpa-0-192.epfl.ch.4713.0
- Xet hash:
- 918f96377d59ddfa7c1181065d063571958e147054e3ea5a0c4b48f5bdb8e34f
- Size of remote file:
- 45 kB
- SHA256:
- 79ceca56c40aeb319482fe5e754fb91a6b5d156035a7892b854603195d3b8189
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