Text Classification
Transformers
English
financial-nlp
sentiment-analysis
topic-classification
multitask-learning
bert
financial-news
Instructions to use farhanage/MTL-FinancialNews-Topic-Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use farhanage/MTL-FinancialNews-Topic-Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="farhanage/MTL-FinancialNews-Topic-Sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("farhanage/MTL-FinancialNews-Topic-Sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download multitask_bert_model_imbalanced.pth from farhanage/MTL-FinancialNews-Topic-Sentiment: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/farhanage/MTL-FinancialNews-Topic-Sentiment/resolve/main/multitask_bert_model_imbalanced.pth
- Command line
-
hf download hf://farhanage/MTL-FinancialNews-Topic-Sentiment/multitask_bert_model_imbalanced.pth
-
curl -L -o multitask_bert_model_imbalanced.pth https://huggingface.co/farhanage/MTL-FinancialNews-Topic-Sentiment/resolve/main/multitask_bert_model_imbalanced.pth
438 MB
- Xet hash:
- 207dab56519166f12818116779da9850fc8eb0cfed05b9a7aa12f1b172c4e3c7
- Size of remote file:
- 438 MB
- SHA256:
- 7768e5360b347271374208fd8b8b0f60171836166d6356ac89df419292e4a6dd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.