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 training_args.bin from Chung-Fan/my_model: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/Chung-Fan/my_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Chung-Fan/my_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Chung-Fan/my_model/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 712625063ce5faba2d8f9e7c910e049dbf065830c7794d86ad790b40c9d67df3
- Size of remote file:
- 3.58 kB
- SHA256:
- 44d84225fe68035049bb8d9bf2e4f37488771c76789f3fd75574bfd8161c5449
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