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 /Dec03_17-25-55_tsf-508-wpa-0-192.epfl.ch /events.out.tfevents.1764779157.tsf-508-wpa-0-192.epfl.ch.4713.1
- Xet hash:
- ae469d517c1a3622aca3370e4a364d4cf9bfc4d1a681e6be6cebb5a8956abf6c
- Size of remote file:
- 22.6 kB
- SHA256:
- 69266f9afafe0918918d9d9e4d894ae7b2c61417092e61eaf61eed426e9823f6
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