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:
- 90bb73a2e65b63d5548b940305e827510b5b2ffc0a19682adbaac7f8768189d1
- Size of remote file:
- 499 MB
- SHA256:
- f3138d0fcc6d09b860905f627ef651e92e0af45bf8e3381b544c52c568376921
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