Instructions to use LyH88/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LyH88/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LyH88/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LyH88/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("LyH88/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0480a1b0f05e2798ad061198cce933ed4e633a1ab19396c4b8aa52b2adf2c9e6
- Size of remote file:
- 268 MB
- SHA256:
- 972d1da5395441585b142bc420f950dd1470a302e4c59cdd40d23ec10df503cc
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