Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use hefeng0/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hefeng0/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hefeng0/dummy-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hefeng0/dummy-model") model = AutoModelForSequenceClassification.from_pretrained("hefeng0/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hefeng0/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/hefeng0/dummy-model/resolve/main/training_args.bin
- Command line
-
hf download hf://hefeng0/dummy-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hefeng0/dummy-model/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 9891747fca79dce5a153b4607123cfd29145b08a38725afb421cc1cf641815f9
- Size of remote file:
- 4.03 kB
- SHA256:
- d55ef9a982218c1e22691d4c165d5fe970307afb538e005539c94cdccf232a77
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