Instructions to use bubai567/nsebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bubai567/nsebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bubai567/nsebert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bubai567/nsebert") model = AutoModelForSequenceClassification.from_pretrained("bubai567/nsebert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from bubai567/nsebert: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/bubai567/nsebert/resolve/main/training_args.bin
- Command line
-
hf download hf://bubai567/nsebert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/bubai567/nsebert/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 70e223dc3b0dafddcb016fd7ecf82dfad7cfa7eaaa1fc6cb570ce2d91b95e442
- Size of remote file:
- 4.03 kB
- SHA256:
- 144d28727362b14bcf87dca706033c2c3a4fd3072268a5b928406ecfbe1cd8b4
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