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:
- 83c471965136b24ded2d60f413af3254d14e0eba0e0425c70a4223d1648c8e2f
- Size of remote file:
- 4.92 kB
- SHA256:
- 2ef84bafa77a1f42be7993ae33390a94a9148cebf447dd6e30de595f7dfb9d4a
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