Instructions to use mdp0999/bert_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mdp0999/bert_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mdp0999/bert_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mdp0999/bert_classification") model = AutoModelForSequenceClassification.from_pretrained("mdp0999/bert_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mdp0999/bert_classification: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/mdp0999/bert_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mdp0999/bert_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mdp0999/bert_classification/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- b23dfd79f3f9c80e8b209f1f594179518b6e47f45b98a919ecbe0b4126a68fcb
- Size of remote file:
- 268 MB
- SHA256:
- be1645704e14bf664d65b85f33317b5518e9074219fc7e24604281b59df28759
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