Instructions to use doublecringe123/lenta-ru-sentiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use doublecringe123/lenta-ru-sentiments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="doublecringe123/lenta-ru-sentiments")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("doublecringe123/lenta-ru-sentiments") model = AutoModelForSequenceClassification.from_pretrained("doublecringe123/lenta-ru-sentiments", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ebb638d8557cbe365a260d46b347cd40f1e5dc48d34a20bbee7972c60a27dd9
- Size of remote file:
- 5.11 kB
- SHA256:
- 784357e5b9ae297945c0d38af94b8e16db4bf1fec6c9c97c8456339fde6d9bac
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