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 pytorch_model.bin from hefeng0/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/hefeng0/dummy-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hefeng0/dummy-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hefeng0/dummy-model/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 0949e120c3a73443b09451b8f9c5446407767d747991e4928778852aeff53e5b
- Size of remote file:
- 438 MB
- SHA256:
- bcbddb0ee3833ff527c7d6f0535d1682a7b0a363f4bbff52a81a542dd9aed3a5
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