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_14-04-29_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764680669.tsf-508-wpa-2-088.epfl.ch.5610.0
- Xet hash:
- 88ebfb2df031e5af59ea09401092e003eb0d77e448da9e442bba8593754f7c32
- Size of remote file:
- 19.6 kB
- SHA256:
- 795c5b89fbc53f657caa7f1b3a33e628e60baff7a494125aa038377b664708e5
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