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:
- 44e3dc9f98f3378c6a9878c263f0b171b7469f3286a9f1e00ac2ee24a5129e13
- Size of remote file:
- 1.47 GB
- SHA256:
- 9e10fcc280143dfac46e6d10cf8f9f56160bc983cf98b0f04cf0859ca2abcf8f
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