Instructions to use shukdevdatta123/twitter-distilbert-base-uncased-sentiment-analysis-lora-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shukdevdatta123/twitter-distilbert-base-uncased-sentiment-analysis-lora-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shukdevdatta123/twitter-distilbert-base-uncased-sentiment-analysis-lora-text-classification")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shukdevdatta123/twitter-distilbert-base-uncased-sentiment-analysis-lora-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a078969aa2c196a06967318b5f6dcfbf122d8c3dfc6c044b8d883ef0d0c923d8
- Size of remote file:
- 5.18 kB
- SHA256:
- 5b36378ff1f79c682e42ecf2d19fcc8078420147775f9fec5dcbb13763e4e88f
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