Translation
Transformers
Safetensors
Arabic
t5
text2text-generation
saudi
arabic
dialects
text-generation-inference
Instructions to use NAMAA-Space/NAMAA-MT-Saudi2English with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NAMAA-Space/NAMAA-MT-Saudi2English 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="NAMAA-Space/NAMAA-MT-Saudi2English")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NAMAA-Space/NAMAA-MT-Saudi2English") model = AutoModelForSeq2SeqLM.from_pretrained("NAMAA-Space/NAMAA-MT-Saudi2English", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ec891af38f5423e015e0aba408f978ec77ee3a82d12975c2d6acaf4029d59a1
- Size of remote file:
- 15.3 MB
- SHA256:
- 64531b1500aefdf7b89d5eda61934a189bec9eff92a99604a56e5557afd9f6b8
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