Instructions to use hf-internal-testing/tiny-random-LEDForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LEDForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LEDForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-LEDForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd8e211d7a4766e54bd32595b121f9acb0bdfadd17e9fdb16a3d6b1593e7e521
- Size of remote file:
- 1.25 MB
- SHA256:
- 1139aa5e2e1ec6f2b4ef7823a616b0b371635bc29646375aa1074554d6ef0104
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