Instructions to use Tanor/BERTicSENTNEG4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/BERTicSENTNEG4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/BERTicSENTNEG4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/BERTicSENTNEG4") model = AutoModelForSequenceClassification.from_pretrained("Tanor/BERTicSENTNEG4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c11a416d59481203da3298a25e1ecdb602290520ade24be86f2a2163745fd16
- Size of remote file:
- 4.98 kB
- SHA256:
- 3f7641122c374e8f41891abca1d7f7218a22295c99afad21821b845fce665dfa
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