Translation
Transformers
PyTorch
Safetensors
m2m_100
text2text-generation
seq2seq
relation-extraction
Instructions to use Babelscape/mrebel-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Babelscape/mrebel-base 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="Babelscape/mrebel-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Babelscape/mrebel-base") model = AutoModelForSeq2SeqLM.from_pretrained("Babelscape/mrebel-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Babelscape/mrebel-base: direct link, hf CLI and curl.
- Browser
- Download file 1.94 GB
-
https://huggingface.co/Babelscape/mrebel-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Babelscape/mrebel-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Babelscape/mrebel-base/resolve/main/pytorch_model.bin
1.94 GB
- Xet hash:
- 32e3d3c7e97a1242f5981bbccab09b674560c077736c57962d96294c0cf36061
- Size of remote file:
- 1.94 GB
- SHA256:
- 94d93abd351a3d1c4463e17cf9bc8dce7a87a4e770a24868b9e792b05a9580d7
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