Instructions to use NLP-FEUP/DA-ProsusAI-finbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP-FEUP/DA-ProsusAI-finbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-FEUP/DA-ProsusAI-finbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NLP-FEUP/DA-ProsusAI-finbert") model = AutoModelForMaskedLM.from_pretrained("NLP-FEUP/DA-ProsusAI-finbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from NLP-FEUP/DA-ProsusAI-finbert: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/NLP-FEUP/DA-ProsusAI-finbert/resolve/main/training_args.bin
- Command line
-
hf download hf://NLP-FEUP/DA-ProsusAI-finbert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/NLP-FEUP/DA-ProsusAI-finbert/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 9481bfb2654e61fa98919ed82571fe018f0a4054b34fd2fd1bf93739efc26922
- Size of remote file:
- 5.18 kB
- SHA256:
- d5f5b93e0eb0cddda0dda83c1b6ba20f33f6db1aaca4b714a9b7ab11e7096d72
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