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 /Nov26_22-40-45_Nurs-Mac.local /events.out.tfevents.1764193247.Nurs-Mac.local.5243.0
- Xet hash:
- e06dad77aecdd9f355eba03e34b6447df357562031bbc3c041a9254175b5128d
- Size of remote file:
- 13.5 kB
- SHA256:
- 0ef4b5265caf8623916f5ea0b7e6e7c893cc8b9f85a65db84a8760bf2f526f6e
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