Instructions to use ilhami/Tr_En-MbartFinetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ilhami/Tr_En-MbartFinetune 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="ilhami/Tr_En-MbartFinetune")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ilhami/Tr_En-MbartFinetune") model = AutoModelForSeq2SeqLM.from_pretrained("ilhami/Tr_En-MbartFinetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94fa9d7f2fbc47b153f6f8e6ebe51ce0d0e6c06da74fba814c31dc76372338c3
- Size of remote file:
- 2.44 GB
- SHA256:
- 55d7be71549ff7042fe26dd450172012cd062dcee6276756db2c2a7dde842312
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