Transformers
PyTorch
TensorFlow
JAX
English
bart
text2text-generation
retrieval
entity-retrieval
named-entity-disambiguation
entity-disambiguation
named-entity-linking
entity-linking
Instructions to use facebook/genre-linking-blink with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/genre-linking-blink with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("facebook/genre-linking-blink") model = AutoModelForSeq2SeqLM.from_pretrained("facebook/genre-linking-blink", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa031d8c867053ca27a014f5b5329f6f9ffb6406d46f55700f1b78e2e6759936
- Size of remote file:
- 1.63 GB
- SHA256:
- d105d545961fe8eec7183bab63dd5dea9acf4cd69783827a4151bda989635d1e
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