Text Classification
Transformers
PyTorch
English
bert
financial-text-analysis
forward-looking-statement
Instructions to use yiyanghkust/finbert-fls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yiyanghkust/finbert-fls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yiyanghkust/finbert-fls")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yiyanghkust/finbert-fls") model = AutoModelForSequenceClassification.from_pretrained("yiyanghkust/finbert-fls") - Inference
- Notebooks
- Google Colab
- Kaggle
Add TF weights
#2
by joaogante - opened
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:67651450ef45a6b6d1e0acad7fec3e3fb5d19ec4105255506a733ecefc656ae1
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size 439304476
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