Instructions to use afsharrad/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afsharrad/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="afsharrad/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("afsharrad/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("afsharrad/finetuning-sentiment-model-3000-samples") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fdd81846509886e27bff0d1c81d02ba085871849f6e59c0dea637458209c508f
- Size of remote file:
- 3.64 kB
- SHA256:
- 2c1e530441c7626e3533f0dfd047376e09b06dbffab5b91e0be54e37756f0c27
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