Instructions to use LucasMagnana/Pictalk_zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LucasMagnana/Pictalk_zero with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="LucasMagnana/Pictalk_zero")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("LucasMagnana/Pictalk_zero") model = AutoModelForMaskedLM.from_pretrained("LucasMagnana/Pictalk_zero") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d4b36f883977f868feda98d2a484519baa22514c78d0e0074d253d07e8a4ea9
- Size of remote file:
- 3.29 MB
- SHA256:
- cb3b255aa0a298491167650b2fbdeb68db1191068c8b6b7b5b17fbc6a5cdeee1
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