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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from almanach/camembertv2-base: direct link, hf CLI and curl.
- Browser
- Download file 551 MB
-
https://huggingface.co/almanach/camembertv2-base/resolve/refs%2Fpr%2F3/tf_model.h5
- Command line
-
hf download hf://almanach/camembertv2-base@refs/pr/3/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/almanach/camembertv2-base/resolve/refs%2Fpr%2F3/tf_model.h5
551 MB
- Xet hash:
- 0a4dee1857ebcea1b72a7004ac6ba566f631fbab60bdfb68f184e86e1c398379
- Size of remote file:
- 551 MB
- SHA256:
- b44b9513de1ab6b3320058b303e9cd8efcf5f53bd3bbf14a5cb418a0c7434505
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