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
Commit History
-
End of Training
2485d4a -
Training in progress epoch 23
98c8455 -
Training in progress epoch 22
d46a70a -
Training in progress epoch 21
612b889 -
Training in progress epoch 20
434234c -
Training in progress epoch 19
c22c5ab -
Training in progress epoch 18
4d954b4 -
Training in progress epoch 17
1784b1a -
Training in progress epoch 16
0eaaf65 -
Training in progress epoch 15
9f9d5c5 -
Training in progress epoch 14
9b0e567 -
Training in progress epoch 13
003ae4d -
Training in progress epoch 12
a2a47b4 -
Training in progress epoch 11
bdfce7b -
Training in progress epoch 10
d7140ef -
Training in progress epoch 9
864d8ee -
Training in progress epoch 8
d0134d2 -
Training in progress epoch 7
708f3a4 -
Training in progress epoch 6
9902f2c -
Training in progress epoch 5
cf371de -
Training in progress epoch 4
1f49aa8 -
Training in progress epoch 3
f83779f -
Training in progress epoch 2
9647742 -
Training in progress epoch 1
54106c1 -
Training in progress epoch 0
267dce0