Instructions to use tr3cks/2LabelsSentimentAnalysisSpanish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tr3cks/2LabelsSentimentAnalysisSpanish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tr3cks/2LabelsSentimentAnalysisSpanish")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tr3cks/2LabelsSentimentAnalysisSpanish") model = AutoModelForSequenceClassification.from_pretrained("tr3cks/2LabelsSentimentAnalysisSpanish") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0dc8e686ba290d56325e57fa538b109dd3cec98ceaf369ec20a48b723f03fd8f
- Size of remote file:
- 439 MB
- SHA256:
- 29e4867b19ff1d8c56e94379d83d3b1773ad081359e64b5784352dd86c623037
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