Translation
Transformers
PyTorch
ONNX
Safetensors
m2m_100
text2text-generation
small100
flores101
gsarti/flores_101
tico19
gmnlp/tico19
tatoeba
Instructions to use alirezamsh/small100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alirezamsh/small100 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="alirezamsh/small100")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alirezamsh/small100") model = AutoModelForSeq2SeqLM.from_pretrained("alirezamsh/small100") - Inference
- Notebooks
- Google Colab
- Kaggle
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Parent(s): ca8a7fb
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README.md
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The model architecture and config are the same as [M2M-100](https://huggingface.co/facebook/m2m100_418M/tree/main) implementation, but the tokenizer is modified to adjust language codes. So, you should load the tokenizer locally from [tokenization_small100.py](https://huggingface.co/alirezamsh/small100/blob/main/tokenization_small100.py) file for the moment.
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Demo is available at: https://huggingface.co/spaces/alirezamsh/small100
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**Note**: SMALL100Tokenizer requires sentencepiece, so make sure to install it by:
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The model architecture and config are the same as [M2M-100](https://huggingface.co/facebook/m2m100_418M/tree/main) implementation, but the tokenizer is modified to adjust language codes. So, you should load the tokenizer locally from [tokenization_small100.py](https://huggingface.co/alirezamsh/small100/blob/main/tokenization_small100.py) file for the moment.
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**Demo**: https://huggingface.co/spaces/alirezamsh/small100
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**Note**: SMALL100Tokenizer requires sentencepiece, so make sure to install it by:
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