Instructions to use h4rr9/mnist_1bit_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use h4rr9/mnist_1bit_new with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, Tim tokenizer = AutoTokenizer.from_pretrained("h4rr9/mnist_1bit_new") model = Tim.from_pretrained("h4rr9/mnist_1bit_new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from h4rr9/mnist_1bit_new: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/h4rr9/mnist_1bit_new/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://h4rr9/mnist_1bit_new/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/h4rr9/mnist_1bit_new/resolve/main/pytorch_model.bin
504 MB
- Xet hash:
- 2269fc7f72b4072619e85f8ca0cc79b3537c900bb8bd1af00d7c74ad3f764003
- Size of remote file:
- 504 MB
- SHA256:
- fb018575cf1b9ca8c2ffb807c91324eb2b0a707ef0372fe1f08d74ed18da1a39
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