Text Classification
Transformers
PyTorch
English
roberta
RoBERTa-large
topic
news
text-embeddings-inference
Instructions to use dell-research-harvard/topic-crime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dell-research-harvard/topic-crime with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dell-research-harvard/topic-crime")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dell-research-harvard/topic-crime") model = AutoModelForSequenceClassification.from_pretrained("dell-research-harvard/topic-crime", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc374a18e6ba03d4d90c54c52f5a0f72bf9b3fc43344a43137ee6766e80c1cea
- Size of remote file:
- 1.42 GB
- SHA256:
- cd544718cfd2baafcf85fc0e78b5f52e78adc38956b0f727c82fe1351830330f
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