Instructions to use Chung-Fan/my_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chung-Fan/my_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Chung-Fan/my_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Chung-Fan/my_model") model = AutoModelForSequenceClassification.from_pretrained("Chung-Fan/my_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Chung-Fan/my_model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Chung-Fan/my_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Chung-Fan/my_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Chung-Fan/my_model/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 3470a8c90b25e1e028e0993c70f810418c5ec35d642931b90fa12ec7bc74d1a0
- Size of remote file:
- 268 MB
- SHA256:
- 425c5b01be67315c43121f6045e9de52dcfc1403b8e0682db3aab8763bf7c98d
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