Instructions to use zera09/bart_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zera09/bart_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zera09/bart_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zera09/bart_classification") model = AutoModelForSequenceClassification.from_pretrained("zera09/bart_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from zera09/bart_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.67 kB
-
https://huggingface.co/zera09/bart_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://zera09/bart_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/zera09/bart_classification/resolve/main/training_args.bin
4.67 kB
- Xet hash:
- e9b083d7965637796718213b2038a067af4e37dc1ccb8528b5d14fd4a747cc1d
- Size of remote file:
- 4.67 kB
- SHA256:
- de753830e13b1d6c8d58d4559b0a18e8467e768ed24a08f4b23f7abac70b0742
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