Translation
Transformers
Safetensors
Arabic
t5
text2text-generation
Syrian
Shami
MT
MSA
Dialect
ArabicNLP
text-generation-inference
Instructions to use Omartificial-Intelligence-Space/Shami-MT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Omartificial-Intelligence-Space/Shami-MT 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")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Omartificial-Intelligence-Space/Shami-MT") model = AutoModelForSeq2SeqLM.from_pretrained("Omartificial-Intelligence-Space/Shami-MT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b0b1da8dc8a0bbf2b1f607d842b6077398a337b4db06139bcbe5414a2987721
- Size of remote file:
- 2.35 MB
- SHA256:
- 180428eb8e88be6c7d259fb04c9eb3a1c552d799a76741bcd6ee34fa0bf64386
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