Instructions to use kabelomalapane/Nso-En_update3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kabelomalapane/Nso-En_update3 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="kabelomalapane/Nso-En_update3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kabelomalapane/Nso-En_update3") model = AutoModelForSeq2SeqLM.from_pretrained("kabelomalapane/Nso-En_update3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download source.spm from kabelomalapane/Nso-En_update3: direct link, hf CLI and curl.
- Browser
- Download file 824 kB
-
https://huggingface.co/kabelomalapane/Nso-En_update3/resolve/main/source.spm
- Command line
-
hf download hf://kabelomalapane/Nso-En_update3/source.spm
-
curl -L -o source.spm https://huggingface.co/kabelomalapane/Nso-En_update3/resolve/main/source.spm
824 kB
- Xet hash:
- 23443712e3ee00ecc1bc4e7cdc2569f8cae4c0d1b1995e124ff1f4b2475bc726
- Size of remote file:
- 824 kB
- SHA256:
- 3d47d9e0c92de38ba56815931a54a13143f9be787ddc83793c7ea390350b58a6
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