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 training_args.bin from Mathissimo/bert_model: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/Mathissimo/bert_model/resolve/ffa540e8ab4c7b9fe5bb9e6d04803fc0ad4bedfa/training_args.bin
- Command line
-
hf download hf://Mathissimo/bert_model@ffa540e8ab4c7b9fe5bb9e6d04803fc0ad4bedfa/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Mathissimo/bert_model/resolve/ffa540e8ab4c7b9fe5bb9e6d04803fc0ad4bedfa/training_args.bin
3.31 kB
- Xet hash:
- c883c212f9071d97f1c09e2417d31c2cbb0b843f1fbe93dd2727190d1ab85292
- Size of remote file:
- 3.31 kB
- SHA256:
- 91556ade324bab106a4e39e12bc4d28d20ef91c423332c2ad8be63a30030fb57
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