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_09-49-22_tsf-508-wpa-6-167.epfl.ch /events.out.tfevents.1764578964.tsf-508-wpa-6-167.epfl.ch.2424.0
- Xet hash:
- 4a75cf37602504f675199f08ef6864c0f70e96d79ef05b63da8f28d191188283
- Size of remote file:
- 15 kB
- SHA256:
- e65d169fad6a0e9e9f75002e47fbd9c10d9b1e3df8820b174d7b2c3d509f85ec
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