Text Classification
Transformers
Safetensors
finance
sentiment-analysis
market-impact
gated-fusion
multitask-learning
event-study
Instructions to use kyLELEng/finimpact-direction1d-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kyLELEng/finimpact-direction1d-v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kyLELEng/finimpact-direction1d-v4")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kyLELEng/finimpact-direction1d-v4", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 258 Bytes
59859a9 | 1 2 3 4 5 6 7 | """
Minimal loading helper for the FinImpact gated fusion checkpoint.
Use this repository with the original training script for the full class definition.
The uploaded model is a custom torch.nn.Module, not a vanilla AutoModelForSequenceClassification.
"""
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