Instructions to use WindyTranslate/translate-ssp-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-ssp-es 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-ssp-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-ssp-es") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-ssp-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-ssp-es, with attribution and change statement
df5999c verified - Xet hash:
- 92aba491852abe3c8215bf4ada951f45d150e67ecb49bbde3a5a5cb64fdb8a56
- Size of remote file:
- 432 kB
- SHA256:
- 44d9219ea204195cacabb7be5f0b9856c4de1548756d044fe715cc240c9480df
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