Instructions to use deepesh0x/bert_wikipedia_sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepesh0x/bert_wikipedia_sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deepesh0x/bert_wikipedia_sst2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("deepesh0x/bert_wikipedia_sst2") model = AutoModelForSequenceClassification.from_pretrained("deepesh0x/bert_wikipedia_sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepesh0x/bert_wikipedia_sst2: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/deepesh0x/bert_wikipedia_sst2/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://deepesh0x/bert_wikipedia_sst2@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepesh0x/bert_wikipedia_sst2/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 70903b9c7eeecd93b751e71f6f0db1ca0979cce138eb7e62f77d7ed7840e1c6d
- Size of remote file:
- 438 MB
- SHA256:
- 41cb485a322b1db1149b5cbd6867616ca4c87e1a9379cc053fe884dc3c7f64d5
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