Instructions to use WindyTranslate/translate-sv-ts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-sv-ts 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-sv-ts")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-sv-ts") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-sv-ts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-sv-ts, with attribution and change statement
973116f verified - Xet hash:
- 16c88c590d184a8433ec454f6db8dc789b8405995ca9b2b6e999503633b64715
- Size of remote file:
- 854 kB
- SHA256:
- bb115bdefa5d271dd51ef52d861a4561fde80e493a779d7a9d5e3fa7135f8f8a
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