Instructions to use sm6342/FinRoberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sm6342/FinRoberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sm6342/FinRoberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sm6342/FinRoberta") model = AutoModelForMaskedLM.from_pretrained("sm6342/FinRoberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96fcd9cbbde57d36dd7171eb1b6cd85ec7b1a64b29f356eff88970dd7ed02bb9
- Size of remote file:
- 334 MB
- SHA256:
- e782e07f885fd72d0f144ae377217555c9fb8fae5c2c3a8a9460ca8af3bd64d9
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