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 /Nov25_08-58-34_tsf-508-wpa-1-223.epfl.ch /events.out.tfevents.1764057515.tsf-508-wpa-1-223.epfl.ch.1964.2
- Xet hash:
- 52538dde1e8ca29c058d30d3eae828b839c34ac436a1b0fb0c424a0a019f897f
- Size of remote file:
- 7.08 kB
- SHA256:
- 265c8e3642afc542873620cbda7a690d007de7d786d9a8eb61b814fce514d203
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