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:
- dbc8921f046ee6846518c20dd8d855d953c49600c3ab1034305ceba5b9ff381c
- Size of remote file:
- 5.43 kB
- SHA256:
- 6078a231a1c6fe0c244d13892e16c8c72862d703dc48cd25ed24687a610d48ea
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