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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9676e69f158ad170ff11f31e0426cb29f0dab6a5df075c583b4db397a47dc600
- Size of remote file:
- 329 MB
- SHA256:
- dcd22977c66107388b5bc9a41928212ae757b8fba82f0426e6b3ae0fb358568c
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