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:
- 566ad1822e385185aaee43bbe9e6df818e02f32edc70e45d5b85aa8dcb9d3947
- Size of remote file:
- 1.11 GB
- SHA256:
- 8ea26bb9f3800f7d713af637dfbd09963ea31b2f73121f6a0ad9bbe0263d2917
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