Instructions to use pere/nb-nn-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pere/nb-nn-dev with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="pere/nb-nn-dev")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pere/nb-nn-dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from pere/nb-nn-dev: direct link, hf CLI and curl.
- Browser
- Download file 1.1 GB
-
https://huggingface.co/pere/nb-nn-dev/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://pere/nb-nn-dev/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/pere/nb-nn-dev/resolve/main/flax_model.msgpack
1.1 GB
- Xet hash:
- ed0dd49138ae21b5e834324a36c9b1f09d81666d6a31a75d2bc9453f41386c3e
- Size of remote file:
- 1.1 GB
- SHA256:
- 898848027a1a64d4a041a1d370de3f24cd865c2c9ba55f0500eb263c07b1c864
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