Instructions to use almanach/camembertv2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almanach/camembertv2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="almanach/camembertv2-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("almanach/camembertv2-base") model = AutoModelForMaskedLM.from_pretrained("almanach/camembertv2-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d4cebc2f67c1a7d5cfc63c54f39322e484faf87553f6ae883e91302008092b0
- Size of remote file:
- 447 MB
- SHA256:
- a3801269fc733109182cf30dc7930be290b654d22a0a3017937175d4223fef8c
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