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 config.json from pere/nb-nn-dev2: direct link, hf CLI and curl.
- Browser
- Download file 688 Bytes
-
https://huggingface.co/pere/nb-nn-dev2/resolve/main/config.json
- Command line
-
hf download hf://pere/nb-nn-dev2/config.json
-
curl -L -o config.json https://huggingface.co/pere/nb-nn-dev2/resolve/main/config.json
688 Bytes
- Xet hash:
- 5789c1241a0a1cbb991cc800ff8f812b5da3c2ec330bb5364915643b0d8fb443
- Size of remote file:
- 688 Bytes
- SHA256:
- b58bfa74027999a2fd69e0201df83f18541b6242a907be04d76537d5f6737373
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.