Instructions to use simonycl/bert-large-uncased-sst-2-16-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonycl/bert-large-uncased-sst-2-16-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simonycl/bert-large-uncased-sst-2-16-13")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simonycl/bert-large-uncased-sst-2-16-13") model = AutoModelForSequenceClassification.from_pretrained("simonycl/bert-large-uncased-sst-2-16-13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from simonycl/bert-large-uncased-sst-2-16-13: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/simonycl/bert-large-uncased-sst-2-16-13/resolve/main/training_args.bin
- Command line
-
hf download hf://simonycl/bert-large-uncased-sst-2-16-13/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/simonycl/bert-large-uncased-sst-2-16-13/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- f01fc964fbf5a0589d9bb6562cb1dc5b4fc227bdb5e8573b9c35dddee75e41fc
- Size of remote file:
- 4.03 kB
- SHA256:
- fff112d2c21f9bbe446081a5584b7161f1f4184067eca9548fdaabfffa7d6651
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