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
twitter-distilbert-base-uncased-sentiment-analysis-lora-text-classification / adapter_model.safetensors
- Xet hash:
- fa1614535004d7e9923c6acd788cd76b8dcfd368cddce8a792eadbf0f6dc743a
- Size of remote file:
- 2.52 MB
- SHA256:
- 71da6f6b1af4516c7d101da3cb1d0dda3c72fbcee39071e0f5252306ab204fda
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