Instructions to use DigitalUmuganda/Quantized_Nllb_Finetuned_Health_En_Kin_8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DigitalUmuganda/Quantized_Nllb_Finetuned_Health_En_Kin_8bit with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DigitalUmuganda/Quantized_Nllb_Finetuned_Health_En_Kin_8bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.bin from DigitalUmuganda/Quantized_Nllb_Finetuned_Health_En_Kin_8bit: direct link, hf CLI and curl.
- Browser
- Download file 1.38 GB
-
https://huggingface.co/DigitalUmuganda/Quantized_Nllb_Finetuned_Health_En_Kin_8bit/resolve/main/model.bin
- Command line
-
hf download hf://DigitalUmuganda/Quantized_Nllb_Finetuned_Health_En_Kin_8bit/model.bin
-
curl -L -o model.bin https://huggingface.co/DigitalUmuganda/Quantized_Nllb_Finetuned_Health_En_Kin_8bit/resolve/main/model.bin
1.38 GB
- Xet hash:
- 56ac709b41c1e3b260fbfb953b5a2b61d396ca98fa5539592830791fa89b98a9
- Size of remote file:
- 1.38 GB
- SHA256:
- a652c991bde671ab47259131f6fc900edf7b2d107c709abff5ccfa8c657a993a
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