Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Felipeit/sentiment-analysis-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Felipeit/sentiment-analysis-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Felipeit/sentiment-analysis-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Felipeit/sentiment-analysis-test") model = AutoModelForSequenceClassification.from_pretrained("Felipeit/sentiment-analysis-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c80c7112583c006992883145d3aee3ff8196fb5fb7ed55bf6dd6877c0df825d
- Size of remote file:
- 1.11 GB
- SHA256:
- 74346938a9a1b6874a40b628ce9feee527ce7971753e8334fd2249ee9f93bca6
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