Instructions to use jplu/tf-camembert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jplu/tf-camembert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jplu/tf-camembert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jplu/tf-camembert-base") model = AutoModelForMaskedLM.from_pretrained("jplu/tf-camembert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Migrate model card from transformers-repo
Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755 Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/jplu/tf-camembert-base/README.md2a40769
-
Update config.json
06efa25
-
Update config.json
f1a0d1b
-
Update sentencepiece.bpe.model
dd8ff3b
-
Update config.json
bc96ca8
-
Update config.json
9ac49dc -
Update tf_model.h5
8f69729 -
Update sentencepiece.bpe.model
59f78cc -
Update config.json
dd13835 -
initial commit
5feaf93