Instructions to use eki1381/practice-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eki1381/practice-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eki1381/practice-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eki1381/practice-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("eki1381/practice-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 852d9c2de9357c0c988d7b9870196dd0dac03f89dfaa39cac931396d69f1e4b0
- Size of remote file:
- 3.31 kB
- SHA256:
- 7ee9d689aaf773b7ffef57fa9060f3fc65d06413372a8a92ccd6c512c5e1a334
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