Instructions to use cardiffnlp/roberta-base-topic-single with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/roberta-base-topic-single with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/roberta-base-topic-single")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/roberta-base-topic-single") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/roberta-base-topic-single", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download metric.json from cardiffnlp/roberta-base-topic-single: direct link, hf CLI and curl.
- Browser
- Download file 230 Bytes
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https://huggingface.co/cardiffnlp/roberta-base-topic-single/resolve/main/metric.json
- Command line
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hf download hf://cardiffnlp/roberta-base-topic-single/metric.json
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curl -L -o metric.json https://huggingface.co/cardiffnlp/roberta-base-topic-single/resolve/main/metric.json
230 Bytes
| {"eval_loss": 0.4330822229385376, "eval_f1": 0.8818665091553456, "eval_f1_macro": 0.7359303318518903, "eval_accuracy": 0.8818665091553456, "eval_runtime": 9.8614, "eval_samples_per_second": 171.68, "eval_steps_per_second": 21.498} |