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:
- 9610705b0ba3cc1fa5078c56673690ed9d8cbc628f816d41abdd72d67d671a52
- Size of remote file:
- 268 MB
- SHA256:
- 0afb4b9a83ee47d01577a17c0725006c11a298fa18bb5506098d279bad357c33
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