Instructions to use pere/nb-nn-dev2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pere/nb-nn-dev2 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-dev2")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pere/nb-nn-dev2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pere/nb-nn-dev2: direct link, hf CLI and curl.
- Browser
- Download file 1.1 GB
-
https://huggingface.co/pere/nb-nn-dev2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://pere/nb-nn-dev2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pere/nb-nn-dev2/resolve/main/pytorch_model.bin
1.1 GB
- Xet hash:
- 3a47d68c2868388272feae2376e9a391ef61b345cc2c24c6f714f835e76eec59
- Size of remote file:
- 1.1 GB
- SHA256:
- 881b699ed1f849f5764af7c95359d38f458e69378f99543c3ecae61c57e9557d
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