Instructions to use NaoS2/multi-kogi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NaoS2/multi-kogi with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NaoS2/multi-kogi") model = AutoModelForSeq2SeqLM.from_pretrained("NaoS2/multi-kogi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from NaoS2/multi-kogi: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/NaoS2/multi-kogi/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NaoS2/multi-kogi/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NaoS2/multi-kogi/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- cf355fa98ec509d4f9b2cc3e4991d4e724de03e0597c3932379b4f484ceac828
- Size of remote file:
- 1.2 GB
- SHA256:
- 7e8fb9ea1156a3a2398b15de6c922ce7697439676b4fdff0a5a44e790f243fb8
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