Instructions to use Anhptp/opus-mt-es-en-BDS-G1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anhptp/opus-mt-es-en-BDS-G1 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="Anhptp/opus-mt-es-en-BDS-G1")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Anhptp/opus-mt-es-en-BDS-G1") model = AutoModelForSeq2SeqLM.from_pretrained("Anhptp/opus-mt-es-en-BDS-G1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1df619d09901b652a0c11d003633487d6d1da49ffdd2949fbcf92f5f8043ae1e
- Size of remote file:
- 310 MB
- SHA256:
- d63358da3797110d76fb8fc05b842997276bd83ef4676a9320cb3653bd88e5b9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.