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_15-49-31_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764686971.tsf-508-wpa-2-088.epfl.ch.7451.0
- Xet hash:
- 7a1f38b11a928581e9ed4ef7b3396ea3dd4e9d299e493066be93fa903f2f2ffd
- Size of remote file:
- 22.2 kB
- SHA256:
- d54b553b7c1dba04b8a2414d14874d891c5d15f883be7fb8f1b3a29c2898c0ec
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