Instructions to use t10gyal/senti_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use t10gyal/senti_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="t10gyal/senti_analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("t10gyal/senti_analysis") model = AutoModelForSequenceClassification.from_pretrained("t10gyal/senti_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49bb0f98e23bae9ea16bc1acff96d305269f4363dcbbb599ddad40e59b5a6bb6
- Size of remote file:
- 268 MB
- SHA256:
- eb94b571873e429bd9fa20abd68a2ebec0d72a8450bc1e234edd079fc327d15c
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