Instructions to use hf-tiny-model-private/tiny-random-MvpForConditionalGeneration 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-MvpForConditionalGeneration 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-MvpForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-MvpForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-MvpForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 123 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MvpForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MvpForConditionalGeneration@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-MvpForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
123 kB
- Xet hash:
- b07227fe0c04ae8f10e3aaccbf948a76c362ef8974ba7f07768b1307b75af3e7
- Size of remote file:
- 123 kB
- SHA256:
- 766d88dd691649a8f9256941ef3b46f0570a1bcb7c2ed12918ae3f3d47044d87
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