Instructions to use WindyTranslate/translate-sn-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sn-sv 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="WindyTranslate/translate-sn-sv")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sn-sv") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sn-sv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sn-sv, with attribution and change statement
18bc9df verified - Xet hash:
- 1bc73a8a91d23c0679969ba53c3d5b321612987658045c5ab33bcb67e68c7a4a
- Size of remote file:
- 834 kB
- SHA256:
- c4b8288453d53185adb604694451fc03ec67d4809d3194bf21c438daf9c89ce4
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