Instructions to use nicktien/TaipeiQA_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nicktien/TaipeiQA_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nicktien/TaipeiQA_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nicktien/TaipeiQA_v1") model = AutoModelForSequenceClassification.from_pretrained("nicktien/TaipeiQA_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nicktien/TaipeiQA_v1: direct link, hf CLI and curl.
- Browser
- Download file 410 MB
-
https://huggingface.co/nicktien/TaipeiQA_v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nicktien/TaipeiQA_v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nicktien/TaipeiQA_v1/resolve/main/pytorch_model.bin
410 MB
- Xet hash:
- ec9547ce6c7d2343e78e15ec804cf010179cf84e65cd8b3b8db33419b226d551
- Size of remote file:
- 410 MB
- SHA256:
- 124e71bc06a70963d5e48d383f6e6e30ff741fc551e92f0758a4f0a5025bdf79
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