Text Classification
Transformers
PyTorch
TensorFlow
JAX
English
bert
financial-sentiment-analysis
sentiment-analysis
Instructions to use ProsusAI/finbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProsusAI/finbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProsusAI/finbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProsusAI/finbert") model = AutoModelForSequenceClassification.from_pretrained("ProsusAI/finbert") - Inference
- Notebooks
- Google Colab
- Kaggle
Add TF weights
#2
by joaogante - opened
Validated by the pt_to_tf CLI. Max crossload hidden state difference=3.123e-05; Max converted hidden state difference=3.123e-05.
Hi there π
I'm a TF maintainer at Hugging Face, and this is your most downloaded (and only) model whose weights can be automatically converted into TensorFlow, using our tools. We believe that having TF weights would be of interest to the community, and will further boost the visibility of the model.
I also don't want to be a source of spam! Let me know if you are interested in merging these TF weights, and if you would like me to open PRs with TF weights for future models that you may own π€
Thank you Joao, it's awesome to also have a TF version of our model!
theofpa changed pull request status to merged