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 /Dec01_16-02-39_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764601359.tsf-508-wpa-6-167.epfl.ch.1783.2
- Xet hash:
- f89672f331831edb48220dd2bd69945a841f270f79a3364cdf8ad0cfe7afa84c
- Size of remote file:
- 25.4 kB
- SHA256:
- 3d6c5631e549607a61a42d2a01b0069ac9538eb2580b593ea0d055c1808c4f7b
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