Instructions to use fergusq/finbert-finnsentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fergusq/finbert-finnsentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fergusq/finbert-finnsentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fergusq/finbert-finnsentiment") model = AutoModelForSequenceClassification.from_pretrained("fergusq/finbert-finnsentiment", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fergusq/finbert-finnsentiment: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/fergusq/finbert-finnsentiment/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fergusq/finbert-finnsentiment/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fergusq/finbert-finnsentiment/resolve/main/pytorch_model.bin
498 MB
- Xet hash:
- cc68684abcce7a928a39ffede73f876404f28def33f26d1d12c0b728c8aafbd2
- Size of remote file:
- 498 MB
- SHA256:
- 68b41c3fce67acb383f70e0c248c54a32e94a23e1bba483311723a2feab5b90d
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