Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use oscarwu/label-transfer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oscarwu/label-transfer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="oscarwu/label-transfer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("oscarwu/label-transfer") model = AutoModelForSequenceClassification.from_pretrained("oscarwu/label-transfer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from oscarwu/label-transfer: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/oscarwu/label-transfer/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://oscarwu/label-transfer@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/oscarwu/label-transfer/resolve/refs%2Fpr%2F2/tokenizer.json
17.1 MB
- Xet hash:
- daa091c8e5762807035867f0bd3c1d7620c175d21571c2785cd59d708ad9cb3a
- Size of remote file:
- 17.1 MB
- SHA256:
- 46afe88da5fd71bdbab5cfab5e84c1adce59c246ea5f9341bbecef061891d0a7
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