Instructions to use sshleifer/bart-large-fp32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/bart-large-fp32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sshleifer/bart-large-fp32")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sshleifer/bart-large-fp32") model = AutoModel.from_pretrained("sshleifer/bart-large-fp32") - Notebooks
- Google Colab
- Kaggle
Update tokenizer_config.json
Browse files- tokenizer_config.json +1 -0
tokenizer_config.json
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{"model_max_length": 1024}
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