Instructions to use egonzalez/classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use egonzalez/classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="egonzalez/classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("egonzalez/classifier") model = AutoModelForMaskedLM.from_pretrained("egonzalez/classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from egonzalez/classifier: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/egonzalez/classifier/resolve/main/tf_model.h5
- Command line
-
hf download hf://egonzalez/classifier/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/egonzalez/classifier/resolve/main/tf_model.h5
438 MB
- Xet hash:
- d4eb635f215c98591653e454d34c510283a9e9b31865f320ca7814e6bd80afba
- Size of remote file:
- 438 MB
- SHA256:
- 95f558ebdbddb18f3f5b11f9a072454c2ecef38166f130e0bc48e30f3408882a
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