Instructions to use dvs/poetry-author-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dvs/poetry-author-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dvs/poetry-author-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dvs/poetry-author-classifier") model = AutoModelForSequenceClassification.from_pretrained("dvs/poetry-author-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from dvs/poetry-author-classifier: direct link, hf CLI and curl.
- Browser
- Download file 609 Bytes
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https://huggingface.co/dvs/poetry-author-classifier/resolve/main/README.md
- Command line
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hf download hf://dvs/poetry-author-classifier/README.md
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curl -L -o README.md https://huggingface.co/dvs/poetry-author-classifier/resolve/main/README.md
609 Bytes
metadata
tags:
- autotrain
- text-classification
widget:
- text: I love AutoTrain
datasets:
- poetry-author-classifier/autotrain-data
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 6.576526641845703
f1_macro: 0.006051911225519596
f1_micro: 0.04395161290322581
f1_weighted: 0.021178625226199167
precision_macro: 0.004909111507595384
precision_micro: 0.04395161290322581
precision_weighted: 0.01643333097832909
recall_macro: 0.012797544111277469
recall_micro: 0.04395161290322581
recall_weighted: 0.04395161290322581
accuracy: 0.04395161290322581