Instructions to use ilan541/OncUponTim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ilan541/OncUponTim with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ilan541/OncUponTim")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ilan541/OncUponTim") model = AutoModelForSequenceClassification.from_pretrained("ilan541/OncUponTim", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from ilan541/OncUponTim: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/ilan541/OncUponTim/resolve/main/tf_model.h5
- Command line
-
hf download hf://ilan541/OncUponTim/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/ilan541/OncUponTim/resolve/main/tf_model.h5
499 MB
- Xet hash:
- adf19e831283336039d3767bd47d2555288c5815c1370737f9e092e6b137563e
- Size of remote file:
- 499 MB
- SHA256:
- fa225646facde4445e0d39e22355c62f122c2fe4ec7fc4cbf76bf59bf67eeac5
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