Instructions to use sshleifer/student_cnn_12_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_cnn_12_2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_cnn_12_2") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_cnn_12_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from sshleifer/student_cnn_12_2: direct link, hf CLI and curl.
- Browser
- Download file 954 MB
-
https://huggingface.co/sshleifer/student_cnn_12_2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://sshleifer/student_cnn_12_2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/sshleifer/student_cnn_12_2/resolve/main/flax_model.msgpack
954 MB
- Xet hash:
- 669eb45c56ea647494c3797f857a558f32f8baab77fd68a42e8c562e9b8f2563
- Size of remote file:
- 954 MB
- SHA256:
- 5db01ad5ff9854e14bd4e36d2abf199ee7bd44e34bba17e431fd19bc1aac3e7b
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