Instructions to use lukecarlate/FinBERT_P_SM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/FinBERT_P_SM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/FinBERT_P_SM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/FinBERT_P_SM") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/FinBERT_P_SM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b75d989b75c082593fcc7e718b81fe842e42a648af4b76cf0707b3859ef5081a
- Size of remote file:
- 438 MB
- SHA256:
- 3f313e60d1971f9e3faeb887c07c9fb3d59e034175cd50bd2cd56886ed483c5e
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