Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use MaxT/poem_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaxT/poem_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MaxT/poem_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MaxT/poem_sentiment") model = AutoModelForSequenceClassification.from_pretrained("MaxT/poem_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1ac734957b745d24acec00bf055e7430bc347aa0f0ef97ace74d47a8650fc4e
- Size of remote file:
- 4.6 kB
- SHA256:
- 9a6982a811e1f012755053cd6ddcf8a75777c73480b45e6ec0b88dfa18774dc1
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