Instructions to use Babelscape/mrebel-large-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Babelscape/mrebel-large-32 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-large-32")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Babelscape/mrebel-large-32") model = AutoModelForSeq2SeqLM.from_pretrained("Babelscape/mrebel-large-32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Babelscape/mrebel-large-32: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/Babelscape/mrebel-large-32/resolve/main/tokenizer.json
- Command line
-
hf download hf://Babelscape/mrebel-large-32/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Babelscape/mrebel-large-32/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 3e4e963fa8fec33597b44c8c881de41ee64f62c1b7607da21276151a274c98a7
- Size of remote file:
- 17.1 MB
- SHA256:
- 0a1b73ee00274d011fd6e01336741d7cb0b7eb018bd86e14aab76b9cf3eaf85a
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