Instructions to use spitfire4794/sarvam-translate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spitfire4794/sarvam-translate 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="spitfire4794/sarvam-translate")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("spitfire4794/sarvam-translate") model = AutoModelForMultimodalLM.from_pretrained("spitfire4794/sarvam-translate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa66c8c017ade193f7cc37a2b421a1fc461563e803f179a496f7bdda2ec42c21
- Size of remote file:
- 33.4 MB
- SHA256:
- 4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
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