Instructions to use vsty/factiverse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vsty/factiverse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vsty/factiverse")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vsty/factiverse") model = AutoModelForSequenceClassification.from_pretrained("vsty/factiverse") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f4b2341e9d8c820293738dce20a0347c76fb867c650ee47f12c08156c505cc5
- Size of remote file:
- 471 MB
- SHA256:
- 770b8dd23d4694f941c97b62642e06cf6df555c93907b1600925cc15656c916f
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