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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ab544fbef421540626cf2b2f0b0dc55b9ac4877a6b952cdc7f70a37ada0f88e
- Size of remote file:
- 8.24 MB
- SHA256:
- f5328fe39a09ddb81738bbf7471999f33a080692c4b7ebabba263b2e40c6781b
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