Instructions to use gabrielkytz/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gabrielkytz/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gabrielkytz/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gabrielkytz/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("gabrielkytz/finetuning-sentiment-model-3000-samples") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14e3aa1065e9b3021533749109a8f9f32c133fcda96c9d4b47eb996418d7b226
- Size of remote file:
- 4.09 kB
- SHA256:
- 6b98e71c048d64be1b71cb39e8d57fbb01768ca73c7cc55ddebffa15b338ff27
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