Instructions to use BERRAMOU/camembert-math-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BERRAMOU/camembert-math-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BERRAMOU/camembert-math-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BERRAMOU/camembert-math-classification") model = AutoModelForSequenceClassification.from_pretrained("BERRAMOU/camembert-math-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BERRAMOU/camembert-math-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/BERRAMOU/camembert-math-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://BERRAMOU/camembert-math-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BERRAMOU/camembert-math-classification/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- 326b2fb7c14f988620cc8deeb3e8d5cba56dc7d688d27503f72eed9e0fa83cf8
- Size of remote file:
- 5.33 kB
- SHA256:
- a24a2f699ff82c5351c481d8040acc718ea658eebbaef72fee2ee2a35a405d00
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