Instructions to use sohidalg/multiun with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sohidalg/multiun 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="sohidalg/multiun")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sohidalg/multiun") model = AutoModelForSeq2SeqLM.from_pretrained("sohidalg/multiun", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3cf3a74937abc06b00f21d750d7a635fe45e7b48c4a00e62e33a6c093b689ede
- Size of remote file:
- 17.1 MB
- SHA256:
- ef126060ddcab67250020d3e4fff2150e3946ba9e7cea24b2a18dd969e0469da
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