Instructions to use hf-internal-testing/tiny-random-PegasusForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PegasusForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PegasusForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-PegasusForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
[Awaiting approval] Upload ONNX weights
#2
by Xenova HF Staff - opened
onnx/decoder_model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:6786bc2ccaff5f26499e0f42a04e6f95e0b101463ebbcf9fd722921f3550f57b
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size 6680207
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onnx/decoder_model_merged.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:119d664dec70d2f262e2b7c71e0f26f7cee395083cfcc2979ad519f642bf2dc2
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size 6775714
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onnx/decoder_with_past_model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:d1438b9ab2951ec725450ff96b183033479c779cd441529a2298b45fea2b2317
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size 6654613
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onnx/encoder_model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:4f164b1b6fb610c81e839d2ba530b88da4b1d23b9efe44c810c8cd55720f21ac
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size 6219599
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