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 parallel_train.json from pere/nb-nn-dev2: direct link, hf CLI and curl.
- Browser
- Download file 19.1 MB
-
https://huggingface.co/pere/nb-nn-dev2/resolve/refs%2Fpr%2F1/parallel_train.json
- Command line
-
hf download hf://pere/nb-nn-dev2@refs/pr/1/parallel_train.json
-
curl -L -o parallel_train.json https://huggingface.co/pere/nb-nn-dev2/resolve/refs%2Fpr%2F1/parallel_train.json
19.1 MB
- Xet hash:
- f3a6bc4258697c9a05d94d80010f675ef1347f99d621a49986ecd6745826d264
- Size of remote file:
- 19.1 MB
- SHA256:
- b9997f562b27af9e7cb412616a01613c466ebd1326bfdee6ae843be507e1b250
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