Instructions to use sanchit-gandhi/tiny-random-bart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanchit-gandhi/tiny-random-bart with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sanchit-gandhi/tiny-random-bart")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sanchit-gandhi/tiny-random-bart") model = AutoModel.from_pretrained("sanchit-gandhi/tiny-random-bart", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from sanchit-gandhi/tiny-random-bart: direct link, hf CLI and curl.
- Browser
- Download file 110 kB
-
https://huggingface.co/sanchit-gandhi/tiny-random-bart/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://sanchit-gandhi/tiny-random-bart/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/sanchit-gandhi/tiny-random-bart/resolve/main/flax_model.msgpack
110 kB
- Xet hash:
- 9a2c69ade99875bbd56c793fea11895a9dea61689a48d95d857fd5479d80bc4b
- Size of remote file:
- 110 kB
- SHA256:
- fc36e10cb2a056cd5f787507d4e6de3217767c8b8246f24d3f1e87abe13310f3
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