Text Classification
Transformers
Safetensors
English
roberta
ag-news
salient-keywords
experiment
text-embeddings-inference
Instructions to use martian786/agnews-salient-random-k16-seed-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use martian786/agnews-salient-random-k16-seed-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="martian786/agnews-salient-random-k16-seed-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("martian786/agnews-salient-random-k16-seed-1") model = AutoModelForSequenceClassification.from_pretrained("martian786/agnews-salient-random-k16-seed-1") - Notebooks
- Google Colab
- Kaggle
| ,World,Sports,Business,Sci/Tech | |
| World,1633,87,112,68 | |
| Sports,47,1794,34,25 | |
| Business,88,36,1548,228 | |
| Sci/Tech,69,33,162,1636 | |