Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use numblilbug/service-rubert-sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use numblilbug/service-rubert-sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="numblilbug/service-rubert-sentiment-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("numblilbug/service-rubert-sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("numblilbug/service-rubert-sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ef570338b9b58c77cca52e70531577e8e2162e5d273cfdf66c8d09cde36da7b
- Size of remote file:
- 4.6 kB
- SHA256:
- 35e3f84f3d26347962adaa1a41c070bb079e1bcb74ce620ef6fce9b7646c368b
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