Instructions to use Outposts/news-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Outposts/news-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Outposts/news-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Outposts/news-classification") model = AutoModelForSequenceClassification.from_pretrained("Outposts/news-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from Outposts/news-classification: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Outposts/news-classification/resolve/main/tf_model.h5
- Command line
-
hf download hf://Outposts/news-classification/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/Outposts/news-classification/resolve/main/tf_model.h5
268 MB
- Xet hash:
- ab1548e51c2885608402331778c7385f70ea15ba77fe758760feb580b35973df
- Size of remote file:
- 268 MB
- SHA256:
- 090bf575e834b468d280f0054fc204f6aff56b8dadcc1145b869e7c9f43df624
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