Instructions to use aequa-tech/sentiment-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aequa-tech/sentiment-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aequa-tech/sentiment-it")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aequa-tech/sentiment-it") model = AutoModelForSequenceClassification.from_pretrained("aequa-tech/sentiment-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from aequa-tech/sentiment-it: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/aequa-tech/sentiment-it/resolve/871b91f02ededfab55740903434f84e2f184c180/rng_state.pth
- Command line
-
hf download hf://aequa-tech/sentiment-it@871b91f02ededfab55740903434f84e2f184c180/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/aequa-tech/sentiment-it/resolve/871b91f02ededfab55740903434f84e2f184c180/rng_state.pth
14.2 kB
- Xet hash:
- f8b5b8585be48967bb013b2e42b90817a195879332da55f9a5d9976c206fc115
- Size of remote file:
- 14.2 kB
- SHA256:
- 6c3682429541cdfcd0fb02189c7dfaf1302c413c5cea42ffd84b55726ff4fcc9
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