Instructions to use blinjrm/finsent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blinjrm/finsent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="blinjrm/finsent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("blinjrm/finsent") model = AutoModelForSequenceClassification.from_pretrained("blinjrm/finsent") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78bd8fe6235649ceda5f6035da1e0671e8420f3e4d6d36b5bcdcb8ba1c039610
- Size of remote file:
- 328 MB
- SHA256:
- d5c9971cfdab61b25a03f6679e58d0b6ffa6b46601a7fc1b3a2b222f081dd37a
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