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_config.json from pere/nb-nn-dev2: direct link, hf CLI and curl.
- Browser
- Download file 394 Bytes
-
https://huggingface.co/pere/nb-nn-dev2/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://pere/nb-nn-dev2/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/pere/nb-nn-dev2/resolve/main/tokenizer_config.json
394 Bytes
- Xet hash:
- 6374ac4dfb08b9758132ca15a2ad07b53a4fc2138edc0201737998275e718edd
- Size of remote file:
- 394 Bytes
- SHA256:
- 1ca0f02ca646d30f4a442c005ecba1769bfcf9ccc8a4c1a07196ee5f30b07631
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