Instructions to use StanKrewinkel/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StanKrewinkel/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="StanKrewinkel/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("StanKrewinkel/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("StanKrewinkel/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ecf3c965386dd34d720b630ca3482f7cbebd590a5a6378e21d9866fa152e2a1
- Size of remote file:
- 3.25 kB
- SHA256:
- b10e65e8605bb3ddb45f5c65be7674df9267e2fb477c13db1b839bbec377d15b
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