Instructions to use explosion-testing/camembert-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use explosion-testing/camembert-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="explosion-testing/camembert-test")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("explosion-testing/camembert-test") model = AutoModelForMaskedLM.from_pretrained("explosion-testing/camembert-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c81d7ffb5ac3cc7479a6a73868826c43cd605ba9e9972550cfa5fba3d7216c04
- Size of remote file:
- 377 kB
- SHA256:
- b68ea171baa4384cb9bfbd5b4dc0a05212cd80daa1878d746a7f6a3751d6a35e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.