Instructions to use Blablablab/10dimensions-romance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Blablablab/10dimensions-romance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Blablablab/10dimensions-romance")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Blablablab/10dimensions-romance") model = AutoModelForSequenceClassification.from_pretrained("Blablablab/10dimensions-romance", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfa8e2e9df4141511d9567d47105a9ae2956bd0ebc873eefafd1f79e0bf567fc
- Size of remote file:
- 433 MB
- SHA256:
- 439911ae32e49db7bb2442c1eaffa2c663c33e6a01db5350e5547c027b53468b
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