Instructions to use almanach/moderncamembert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almanach/moderncamembert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="almanach/moderncamembert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("almanach/moderncamembert-base") model = AutoModelForMaskedLM.from_pretrained("almanach/moderncamembert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from almanach/moderncamembert-base: direct link, hf CLI and curl.
- Browser
- Download file 545 MB
-
https://huggingface.co/almanach/moderncamembert-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://almanach/moderncamembert-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/almanach/moderncamembert-base/resolve/main/pytorch_model.bin
545 MB
- Xet hash:
- 0d7a4ce02adb1de8471d4d5d5d516ef7f6b039210a1d0d7ebfe78e36acbe631f
- Size of remote file:
- 545 MB
- SHA256:
- adc2acc4f88a96513012d843a147be008ab6aff1559d1a67a139c17b720b0dd4
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