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 pytorch_model.bin from bubai567/nsebert: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/bubai567/nsebert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bubai567/nsebert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bubai567/nsebert/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- d7efbe27bb8a3a9a56aa300d731f6b009508ed1d75050fb670090f4ef3a32825
- Size of remote file:
- 438 MB
- SHA256:
- fd2904c52d6a66a17ef65c1e0f2522d0b5e19c421781e06c982a6931b73a2148
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