Translation
Transformers
PyTorch
Safetensors
English
Turkish
marian
text2text-generation
medical
medical translation
Instructions to use aimped/nlp-health-translation-base-en-tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aimped/nlp-health-translation-base-en-tr 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="aimped/nlp-health-translation-base-en-tr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("aimped/nlp-health-translation-base-en-tr") model = AutoModelForSeq2SeqLM.from_pretrained("aimped/nlp-health-translation-base-en-tr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Access aimped/nlp-health-translation-base-en-tr on Hugging Face
This is a form to enable access to this model on Hugging Face after you have been granted access from the Aimped. Please visit the Aimped website to Sign Up and accept our Terms of Use and Privacy Policy before submitting this form. Requests will be processed in 1-2 days.
Your Hugging Face account email address MUST match the email you provide on the Aimped website or your request will not be approved.
Log in or Sign Up to review the conditions and access this model content.
Gated model You can list files but not access them
Preview of files found in this repository