Instructions to use sshleifer/student_cnn_12_9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_cnn_12_9 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_cnn_12_9") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_cnn_12_9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from sshleifer/student_cnn_12_9: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/sshleifer/student_cnn_12_9/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://sshleifer/student_cnn_12_9/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/sshleifer/student_cnn_12_9/resolve/main/flax_model.msgpack
1.42 GB
- Xet hash:
- 77ba1d00a6118013c199955a8aff079913de0fef6ecce7b287e86b7a20756cc3
- Size of remote file:
- 1.42 GB
- SHA256:
- 94a9dea7fb8ceb6ef883ea4882bd20546f232250920944c9fa1552348b6a28ec
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