Instructions to use AgentPublic/dpr-question_encoder-fr_qa-camembert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AgentPublic/dpr-question_encoder-fr_qa-camembert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AgentPublic/dpr-question_encoder-fr_qa-camembert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AgentPublic/dpr-question_encoder-fr_qa-camembert") model = AutoModel.from_pretrained("AgentPublic/dpr-question_encoder-fr_qa-camembert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0fd6e9d54e917081d7a391ec74fbd36d571df0b07f12d5311333ab96d6f54d43
- Size of remote file:
- 443 MB
- SHA256:
- dc1ae262d689f595cc7d622961e32a1eda6dc4a02d7edee83a385917a4fb611d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.