Text Classification
Transformers
PyTorch
roberta
topic
classification
news
Eval Results (legacy)
text-embeddings-inference
Instructions to use dstefa/roberta-base_topic_classification_nyt_news with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dstefa/roberta-base_topic_classification_nyt_news with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dstefa/roberta-base_topic_classification_nyt_news")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dstefa/roberta-base_topic_classification_nyt_news") model = AutoModelForSequenceClassification.from_pretrained("dstefa/roberta-base_topic_classification_nyt_news", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dstefa/roberta-base_topic_classification_nyt_news: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/dstefa/roberta-base_topic_classification_nyt_news/resolve/main/training_args.bin
- Command line
-
hf download hf://dstefa/roberta-base_topic_classification_nyt_news/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dstefa/roberta-base_topic_classification_nyt_news/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 3dbb094490b3ce2a26e91099290de50a1bacb2f9bcd3eca934a6cb0073b054f5
- Size of remote file:
- 4.6 kB
- SHA256:
- 6e634b15fce4d55ea8cc8787cb28202df1913f7d700c642c7d835594210f201e
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