Instructions to use Deepakvictor/tan-ta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deepakvictor/tan-ta 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="Deepakvictor/tan-ta")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Deepakvictor/tan-ta") model = AutoModelForSeq2SeqLM.from_pretrained("Deepakvictor/tan-ta") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:dddad70787e42e02dc3f765017d85ccd09fc9a37539f1b200ce1dd336c3e352a
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size 1935681888
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