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/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Mathissimo/bert_model@refs/pr/1/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Mathissimo/bert_model/resolve/refs%2Fpr%2F1/training_args.bin
3.31 kB
- Xet hash:
- ee6b83a8f50a515e7b9f51efca5afe54ee94e8c7098cf26fdec08708fed36651
- Size of remote file:
- 3.31 kB
- SHA256:
- 5f8115b1d7d16d0e72de2e2f14ff06a84781da5088b3e04eb6fa575eb38f38f6
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