Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use wnic00/saya_test_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wnic00/saya_test_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wnic00/saya_test_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wnic00/saya_test_sentiment") model = AutoModelForSequenceClassification.from_pretrained("wnic00/saya_test_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25f00c99ffdd046866a8f63ef8fb5db48719549af2dafa6a03fc74a5e1d15bf1
- Size of remote file:
- 3.96 kB
- SHA256:
- 2ebc49fe3ea1ef84e52aba73785018b4054e4834a5d3e8f56a93e73ad362bcaa
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