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_17-13-09_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764691990.tsf-508-wpa-2-088.epfl.ch.8916.1
- Xet hash:
- bc33d011aee6fdc8b87ac64831ef254318bb1258a099343ac69fc3589c57ed26
- Size of remote file:
- 10.1 kB
- SHA256:
- a9e4cf36e603377bce07b8693a26f91127290cfe45ddaf46eb5e1c74c23f8c36
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