Instructions to use hf-tiny-model-private/tiny-random-LongT5ForConditionalGeneration 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-LongT5ForConditionalGeneration with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LongT5ForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-LongT5ForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-LongT5ForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 4.47 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-LongT5ForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-LongT5ForConditionalGeneration@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-LongT5ForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
4.47 MB
- Xet hash:
- ad2007753f6c08e0d4205a38b467c185e3c1c5a945b41843d80e6d05092c7580
- Size of remote file:
- 4.47 MB
- SHA256:
- 9a3240a61b9aa39ec314c3f1d52a166000b8c289da5c6500c6d4a5eca6244ccb
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