Instructions to use allegro/herbert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allegro/herbert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="allegro/herbert-base-cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("allegro/herbert-base-cased") model = AutoModel.from_pretrained("allegro/herbert-base-cased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from allegro/herbert-base-cased: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/allegro/herbert-base-cased/resolve/108138c2ae3ae7cd4d04261c1a3b128e1cf0d3f1/flax_model.msgpack
- Command line
-
hf download hf://allegro/herbert-base-cased@108138c2ae3ae7cd4d04261c1a3b128e1cf0d3f1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/allegro/herbert-base-cased/resolve/108138c2ae3ae7cd4d04261c1a3b128e1cf0d3f1/flax_model.msgpack
498 MB
- Xet hash:
- 5ee67a43239502e223a34857ecfe735835cd69f68d6351f52c3b0d4f256f3a5c
- Size of remote file:
- 498 MB
- SHA256:
- 1ac9833e53325a5ae334b58e47cdd70fc5b37b7b62e436351eba89e6448ad710
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