Instructions to use zeromodels/t5_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/t5_small with ZeroModels:
# pip install -U zeromodels # ZeroModels is pure Keras 3, so pick a backend: "jax", "torch" or "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" from zeromodels import AutoZModel # AutoZModel reads the repo's model_type and loads the matching class. # For a task head use the matching loader, e.g. AutoZMImageClassify / AutoZMDetect / # AutoZMSemanticSegment / AutoZMTextGenerate (see zeromodels.auto). model = AutoZModel.from_weights("zeromodels/t5_small") - Keras
How to use zeromodels/t5_small with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://zeromodels/t5_small") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from zeromodels/t5_small: direct link, hf CLI and curl.
- Browser
- Download file 1.39 MB
-
https://huggingface.co/zeromodels/t5_small/resolve/main/tokenizer.json
- Command line
-
hf download hf://zeromodels/t5_small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/zeromodels/t5_small/resolve/main/tokenizer.json
1.39 MB
File too large to display, you can check the raw version instead.