Instructions to use hf-internal-testing/tiny-random-M2M100ForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-M2M100ForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-M2M100ForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-M2M100ForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c3eae74b4a6720fe219081bbf0ad4c7bd7666731f5677d4f8acad2125ccbd32
- Size of remote file:
- 8.3 MB
- SHA256:
- c96ba9cf5716ff051642481cabc5f6e8969e85cda7d94a83ef46c246ac4f9e3c
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