Instructions to use almanach/camembert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almanach/camembert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="almanach/camembert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("almanach/camembert-base") model = AutoModelForMaskedLM.from_pretrained("almanach/camembert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
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It is now available on Hugging Face in 6 different versions with varying number of parameters, amount of pretraining data and pretraining data source domains.
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For further information or requests, please go to [Camembert Website](https://camembert-model.fr/)
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## Pre-trained models
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| Model | #params | Arch. | Training data |
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It is now available on Hugging Face in 6 different versions with varying number of parameters, amount of pretraining data and pretraining data source domains.
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## Pre-trained models
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| Model | #params | Arch. | Training data |
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