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 npk_train.json from pere/nb-nn-dev2: direct link, hf CLI and curl.
- Browser
- Download file 24.2 MB
-
https://huggingface.co/pere/nb-nn-dev2/resolve/main/npk_train.json
- Command line
-
hf download hf://pere/nb-nn-dev2/npk_train.json
-
curl -L -o npk_train.json https://huggingface.co/pere/nb-nn-dev2/resolve/main/npk_train.json
24.2 MB
- Xet hash:
- b43b7b018d90843e26ca17f00f079583a874b47e9ba35cabf4be0c2f2834cbda
- Size of remote file:
- 24.2 MB
- SHA256:
- 5edbf831e8bf71989f724725c47ed52f3fc0ba976ac5e7e69a93a37917b22ac3
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