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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("almanach/camembert-base") model = AutoModelForMaskedLM.from_pretrained("almanach/camembert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from almanach/camembert-base: direct link, hf CLI and curl.
- Browser
- Download file 543 MB
-
https://huggingface.co/almanach/camembert-base/resolve/refs%2Fpr%2F10/tf_model.h5
- Command line
-
hf download hf://almanach/camembert-base@refs/pr/10/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/almanach/camembert-base/resolve/refs%2Fpr%2F10/tf_model.h5
543 MB
- Xet hash:
- 7f240f1f6013511e1d9381e676e85a47dc33e77d776e9290e3f5828b9c7f6f87
- Size of remote file:
- 543 MB
- SHA256:
- 1a7be48987fe8c135cb985e9b0f07cc5c14d3b1b934b7fd16f4844a3b3e884a9
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