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_17-18-24_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764692304.tsf-508-wpa-2-088.epfl.ch.8916.2
- Xet hash:
- d0fffc74b49138e7dda4305a7d08e93514e48d1b79172fd82c3f8345ac4a1842
- Size of remote file:
- 45 kB
- SHA256:
- 75abaf5206927d2c99d6e3f8ebc20a535c8477e86a38d18514d53eb9352abe96
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