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:
- 30c4732a6436391767247e90597f106aac8048001d1d0be8c1ba61e35fbff98b
- Size of remote file:
- 3.45 kB
- SHA256:
- de05124cc3ec9b05573bc4ae53b17305edd5c8c443a6fe6d67139aa6651a6929
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