Instructions to use sshleifer/bart-tiny-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/bart-tiny-random with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/bart-tiny-random") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/bart-tiny-random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sshleifer/bart-tiny-random: direct link, hf CLI and curl.
- Browser
- Download file 5.11 MB
-
https://huggingface.co/sshleifer/bart-tiny-random/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sshleifer/bart-tiny-random/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sshleifer/bart-tiny-random/resolve/main/pytorch_model.bin
5.11 MB
- Xet hash:
- b1d3f4f14e9d181bcdab4ebf0f35f56c358aac5e9dd2d9ceebd2e87bf4aac8c3
- Size of remote file:
- 5.11 MB
- SHA256:
- d14e2182f0d6662d88cc0976c8fa04c2aab8634115a238b09458e6e1334b5770
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