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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1e184e473b64c03d2979f8b3fb46ca28f6295d87b99a428a48820f547eb296e
- Size of remote file:
- 5.27 kB
- SHA256:
- d3bf5789497aeb9dde5f757914e12ec101b234de047a1d0df789825a513676b4
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