Instructions to use rarmingaud/ManufactuBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rarmingaud/ManufactuBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="rarmingaud/ManufactuBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("rarmingaud/ManufactuBERT") model = AutoModelForMaskedLM.from_pretrained("rarmingaud/ManufactuBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cbd6883a52d4737a6bd23e389ffe9acea4472fd49838744fd47b89eeaa4e960a
- Size of remote file:
- 499 MB
- SHA256:
- d45eda626808be60209eb23631cd9c77e77e60e0db16b6889812a1678e5296f2
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