Instructions to use Freceerwin/sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Freceerwin/sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Freceerwin/sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Freceerwin/sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("Freceerwin/sentiment-analysis") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4f0260a0ec03e6c6f74b3c66254c72dbca31a2b934d0282bc2129247ed0d825a
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size 651404300
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