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 tokenizer_config.json from fergusq/finbert-finnsentiment: direct link, hf CLI and curl.
- Browser
- Download file 29 Bytes
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https://huggingface.co/fergusq/finbert-finnsentiment/resolve/e5b51344258e0bcdc89fb757621bc4df9f88940e/tokenizer_config.json
- Command line
-
hf download hf://fergusq/finbert-finnsentiment@e5b51344258e0bcdc89fb757621bc4df9f88940e/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/fergusq/finbert-finnsentiment/resolve/e5b51344258e0bcdc89fb757621bc4df9f88940e/tokenizer_config.json
29 Bytes
| { | |
| "do_lower_case": false | |
| } | |