Instructions to use Fsoft-AIC/dopamin-post-training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fsoft-AIC/dopamin-post-training with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fsoft-AIC/dopamin-post-training")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fsoft-AIC/dopamin-post-training") model = AutoModelForSequenceClassification.from_pretrained("Fsoft-AIC/dopamin-post-training", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 558ea6d4e0feb1423849036a2ca9212a1a919a7bb7f0e0b08881c4de61a0d69f
- Size of remote file:
- 4.22 kB
- SHA256:
- 695ac2c839271c3749092c47adcf8c2c9f4126b583662ecf48d6766b70d1c279
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