Instructions to use hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49d229b026768966b54dd595d8432045099b85e28044d2ac09c99bf6bbd31d88
- Size of remote file:
- 4.06 MB
- SHA256:
- 5d15bac92e59a0195fee198effde4904108217e24e6cff81c56e12117b1ff9be
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