Instructions to use kejian/immaculate-mle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kejian/immaculate-mle with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kejian/immaculate-mle") model = AutoModel.from_pretrained("kejian/immaculate-mle", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kejian/immaculate-mle: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/kejian/immaculate-mle/resolve/main/training_args.bin
- Command line
-
hf download hf://kejian/immaculate-mle/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kejian/immaculate-mle/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- 28cf8bac2fc78531a06a3d9a06f63da3324d18bd931b68f36d67c9459d1d26ad
- Size of remote file:
- 3.39 kB
- SHA256:
- f4981a12fc597c69732b1784c47736ca66e671684e8d4e5a8f488d5ed39c513e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.