Instructions to use Mathissimo/bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathissimo/bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mathissimo/bert_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mathissimo/bert_model") model = AutoModelForSequenceClassification.from_pretrained("Mathissimo/bert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mathissimo/bert_model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Mathissimo/bert_model/resolve/ffa540e8ab4c7b9fe5bb9e6d04803fc0ad4bedfa/pytorch_model.bin
- Command line
-
hf download hf://Mathissimo/bert_model@ffa540e8ab4c7b9fe5bb9e6d04803fc0ad4bedfa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mathissimo/bert_model/resolve/ffa540e8ab4c7b9fe5bb9e6d04803fc0ad4bedfa/pytorch_model.bin
268 MB
- Xet hash:
- 04d913f8bbfada37a122b54873a526dbe341b7b571f6063a25729db96902061f
- Size of remote file:
- 268 MB
- SHA256:
- 78037aca98a53b21f5fd1c317d5da090edf2cf49ab8423652884046a3c0a3e41
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