Translation
Transformers
Safetensors
Arabic
t5
text2text-generation
Syrian
Shami
MT
MSA
Dialect
ArabicNLP
text-generation-inference
Instructions to use Omartificial-Intelligence-Space/SHAMI-MT-2MSA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Omartificial-Intelligence-Space/SHAMI-MT-2MSA 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="Omartificial-Intelligence-Space/SHAMI-MT-2MSA")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Omartificial-Intelligence-Space/SHAMI-MT-2MSA") model = AutoModelForSeq2SeqLM.from_pretrained("Omartificial-Intelligence-Space/SHAMI-MT-2MSA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a21a61e5232580558762f3e54f925988b8d299a07fccec55e2e7c2aae5c7580
- Size of remote file:
- 15.3 MB
- SHA256:
- 8f44edc170f46f7b935e2f9300730d57d01bea690f2f9e9e480cdd09017595fc
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