Instructions to use Xtiphyn/News-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xtiphyn/News-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Xtiphyn/News-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Xtiphyn/News-classification") model = AutoModelForSequenceClassification.from_pretrained("Xtiphyn/News-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Xtiphyn/News-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.75 kB
-
https://huggingface.co/Xtiphyn/News-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://Xtiphyn/News-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Xtiphyn/News-classification/resolve/main/training_args.bin
5.75 kB
- Xet hash:
- e90968bcdb1f599e1015e4302b3056f63df512faff49e738a6a3c1fe5a37929c
- Size of remote file:
- 5.75 kB
- SHA256:
- 880b85567f6201c637f088c448f2ceacfa5787f5be9fc0b47e91b4a683204836
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.