Instructions to use sshleifer/student_cnn_12_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_cnn_12_6 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_cnn_12_6") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_cnn_12_6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from sshleifer/student_cnn_12_6: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/sshleifer/student_cnn_12_6/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://sshleifer/student_cnn_12_6/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/sshleifer/student_cnn_12_6/resolve/main/flax_model.msgpack
1.22 GB
- Xet hash:
- bfaea1606879a51198cd15ecc42c6f0af9da6843dc20fdd1bf0d5b8a72060525
- Size of remote file:
- 1.22 GB
- SHA256:
- 3b5f386d30bb3cebd906a20274fa3054d37ab25e80dfd1417eb8b7d2501c9486
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