Instructions to use torresflo/Poke-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use torresflo/Poke-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="torresflo/Poke-Model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("torresflo/Poke-Model") model = AutoModelForImageClassification.from_pretrained("torresflo/Poke-Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from torresflo/Poke-Model: direct link, hf CLI and curl.
- Browser
- Download file 344 MB
-
https://huggingface.co/torresflo/Poke-Model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://torresflo/Poke-Model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/torresflo/Poke-Model/resolve/main/pytorch_model.bin
344 MB
- Xet hash:
- 5ce472a89ec8bbf96c2200baaf09fc4191ddfd18029a18a9b12d6f883546ed9c
- Size of remote file:
- 344 MB
- SHA256:
- d2929fbc8787b6ec07f9d2dcafa6d39aec7fdced704654792999929621ca402e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.