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_14-58-20_tsf-508-wpa-2-088.epfl.ch /events.out.tfevents.1764683900.tsf-508-wpa-2-088.epfl.ch.6884.0
- Xet hash:
- efc66076da8412487639a20a46d6748251bc89a80c5ba63fe2ad657306102887
- Size of remote file:
- 19.6 kB
- SHA256:
- 7d2df7f195aeaeb8ff89df5193f8fcc23fd9706b62d6418d54f2b8bde98594df
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