Instructions to use teera-biotech/Hack5-train-train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use teera-biotech/Hack5-train-train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="teera-biotech/Hack5-train-train") 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("teera-biotech/Hack5-train-train") model = AutoModelForImageClassification.from_pretrained("teera-biotech/Hack5-train-train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from teera-biotech/Hack5-train-train: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/teera-biotech/Hack5-train-train/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://teera-biotech/Hack5-train-train/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/teera-biotech/Hack5-train-train/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- a17f60994eeeea59ee8214cf35a055bf5202b6023dea4bacfb7b9129519a9cac
- Size of remote file:
- 343 MB
- SHA256:
- acdede3545448a571ab68923f5ba9b6717a7d10beea1d4fe55e805da29d2c2c1
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