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:
- 510849e43dca5b44d7581bdb9e234fe847fd26653a1d04f2e5d34aa62428124b
- Size of remote file:
- 499 MB
- SHA256:
- d9dd5fe4a062e8c44c52c72822a1ba709143d97aa863da661a11a04741c9c807
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