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_10-30-36_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764667836.tsf-508-wpa-2-088.epfl.ch.1560.1
- Xet hash:
- a68f70e21cea11847f7c54e3ba6d0f5b45b513b34535d345c6d57567a6e1e16c
- Size of remote file:
- 19.6 kB
- SHA256:
- 03bb15c598118ba01d6d1b054654ab08567ba281333a92a3e62beaa64a7656d2
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