Instructions to use NLP-FEUP/FT-ProsusAI-finbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP-FEUP/FT-ProsusAI-finbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NLP-FEUP/FT-ProsusAI-finbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NLP-FEUP/FT-ProsusAI-finbert") model = AutoModelForSequenceClassification.from_pretrained("NLP-FEUP/FT-ProsusAI-finbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from NLP-FEUP/FT-ProsusAI-finbert: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/NLP-FEUP/FT-ProsusAI-finbert/resolve/main/training_args.bin
- Command line
-
hf download hf://NLP-FEUP/FT-ProsusAI-finbert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/NLP-FEUP/FT-ProsusAI-finbert/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 3155c08c5da6c03a23339e3b4424dfdc2a46a9c8f06707d63930bb46cca156d1
- Size of remote file:
- 5.18 kB
- SHA256:
- f85c53110d402e24243d778631eda5e5971cb1af0a370779b645f30c1eacdcc5
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