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 /Nov26_14-46-59_tsf-508-wpa-3-037.epfl.ch /events.out.tfevents.1764164825.tsf-508-wpa-3-037.epfl.ch.4455.0
- Xet hash:
- e0e77092831ceb5085620ac0ad223635ee7d0ef1fb1a0cd65625e0b1b3295303
- Size of remote file:
- 13.6 kB
- SHA256:
- 2bd5d5ba285c84c539c1e01cec674c3d7523458ab010870dfb1091b45a4f992b
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