Instructions to use Nextcloud-AI/opus-mt-tr-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nextcloud-AI/opus-mt-tr-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="Nextcloud-AI/opus-mt-tr-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Nextcloud-AI/opus-mt-tr-es") model = AutoModelForSeq2SeqLM.from_pretrained("Nextcloud-AI/opus-mt-tr-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99198c736085a90e3b38f17c8a3141232dfff2d10619d27f8c9647dc9e92e2c6
- Size of remote file:
- 301 MB
- SHA256:
- fa7571bacbc932a3758a1f7d72bc48ed566b9319576a144d4f189e342ed09578
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