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 tokenizer.json from pere/nb-nn-dev2: direct link, hf CLI and curl.
- Browser
- Download file 8.31 MB
-
https://huggingface.co/pere/nb-nn-dev2/resolve/main/tokenizer.json
- Command line
-
hf download hf://pere/nb-nn-dev2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/pere/nb-nn-dev2/resolve/main/tokenizer.json
8.31 MB
- Xet hash:
- 528fec68b86796ca22febd78f5a4a351370a82dea47779d93e089919de4883be
- Size of remote file:
- 8.31 MB
- SHA256:
- a45a3502ba77d86b2ffb251212b1db55b926c5c1da45cf5462a60051b8eb96fe
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