Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Giova-tech/sentiment-analysis-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Giova-tech/sentiment-analysis-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Giova-tech/sentiment-analysis-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Giova-tech/sentiment-analysis-test") model = AutoModelForSequenceClassification.from_pretrained("Giova-tech/sentiment-analysis-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 425773fe769e80ab12c9ba51b9fad28365dbc0e7f95c9580308d1b4b4956877f
- Size of remote file:
- 5.3 kB
- SHA256:
- f70d888a20c7eef11e216d1682ff4c4d8bc5001ba4562a60f1c626030d71244e
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