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")# 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") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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oid sha256:3b20cb16529923a3a587ad28ec6fd54660b55acbcf5619830ef7c77e683cd488
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size 498631280
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