Instructions to use allegro/herbert-large-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allegro/herbert-large-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="allegro/herbert-large-cased")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("allegro/herbert-large-cased") model = AutoModel.from_pretrained("allegro/herbert-large-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa1fe7a8f85bab8b6386bcabb804ffe8a1df8cb103f2b149e3584e6d5b6df423
- Size of remote file:
- 1.42 GB
- SHA256:
- 66bacb3455481bd3fdd4d125abba6da580625fcbfe933115005a462742b8d369
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