Instructions to use lukecarlate/SecBERT_CM_Num with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/SecBERT_CM_Num with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/SecBERT_CM_Num")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/SecBERT_CM_Num") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/SecBERT_CM_Num") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6fc58a38679534c8eef9f9baded6a5ed44b477b7c02a0a3a39cae1755333fc7d
- Size of remote file:
- 3 kB
- SHA256:
- ac7cca96d426c9d9c989671c009b74ad79b518d5ca2f9a2ffdcf6762b7d32e5f
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