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:
- 3ac7920fa57dd2cc0c3bdcb9a3dce1cbf994b0faf034aac2f451c25543992ade
- Size of remote file:
- 268 MB
- SHA256:
- f0ebd4c222169c8bdc6450305b7f70cc3a79987764037bf6fe21a4b5c16ae02b
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