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
- Xet hash:
- f6b2432001389a6f9cf27f1c43eb78d76058160a55141878a525c4de67c37fe0
- Size of remote file:
- 2.42 MB
- SHA256:
- d8f7c76ed2a5e0822be39f0a4f95a55eb19c78f4593ce609e2edbc2aea4d380a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.