Instructions to use HPLT/hplt_bert_base_fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_fr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_fr", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_fr", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc65c21462772845d62f6f856dec5f69a1cd0c20d36923c6229a9a28909575e2
- Size of remote file:
- 525 MB
- SHA256:
- eb576ade0ba583779195fdaec0fb5051d35fc48e28ef0c906f4a3bfc7cde8c93
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.