Instructions to use Davidwang215/TEM_USE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davidwang215/TEM_USE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="Davidwang215/TEM_USE")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Davidwang215/TEM_USE") model = AutoModel.from_pretrained("Davidwang215/TEM_USE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Davidwang215/TEM_USE: direct link, hf CLI and curl.
- Browser
- Download file 3.64 MB
-
https://huggingface.co/Davidwang215/TEM_USE/resolve/main/tokenizer.json
- Command line
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hf download hf://Davidwang215/TEM_USE/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Davidwang215/TEM_USE/resolve/main/tokenizer.json
3.64 MB
File too large to display, you can check the raw version instead.