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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29d8b99f7d29ae8e1c85b330c9b1db0942052f370c9f8f809da456ac43e25391
- Size of remote file:
- 4.09 kB
- SHA256:
- 85c1a63dfbd55034ba794aa06f6672556115d87109d6a6c740d9c8bdb24187ea
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