Instructions to use dejanseo/sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dejanseo/sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dejanseo/sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dejanseo/sentiment") model = AutoModelForSequenceClassification.from_pretrained("dejanseo/sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 922e099f95a6c6ed320a72125997f0a2d0fc1421b1a4aeabc7a824f7f07974d1
- Size of remote file:
- 14.2 kB
- SHA256:
- eaf7361eaba266493774b86d64b97ccfa7c8e3649ff56cfcc431422b4296fa35
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.