Instructions to use NLP-FEUP/DA-FT-ProsusAI-finbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP-FEUP/DA-FT-ProsusAI-finbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NLP-FEUP/DA-FT-ProsusAI-finbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NLP-FEUP/DA-FT-ProsusAI-finbert") model = AutoModelForSequenceClassification.from_pretrained("NLP-FEUP/DA-FT-ProsusAI-finbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from NLP-FEUP/DA-FT-ProsusAI-finbert: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/NLP-FEUP/DA-FT-ProsusAI-finbert/resolve/main/training_args.bin
- Command line
-
hf download hf://NLP-FEUP/DA-FT-ProsusAI-finbert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/NLP-FEUP/DA-FT-ProsusAI-finbert/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 7ac95ad89a28741a85fe7092a12f2f447cf18d204f0436017f4c6b698bfd2c54
- Size of remote file:
- 5.18 kB
- SHA256:
- b6e72f944fbd2fb303d4efc9635a3eca48096f472e1d85e0b7b3aedad9de126c
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