Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use TieIncred/verizon_model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TieIncred/verizon_model1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TieIncred/verizon_model1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TieIncred/verizon_model1") model = AutoModelForSequenceClassification.from_pretrained("TieIncred/verizon_model1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TieIncred/verizon_model1: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/TieIncred/verizon_model1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TieIncred/verizon_model1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TieIncred/verizon_model1/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 4b30fcd0ec0ac76e0c1ae0212b08e8a7ccb35cead581dbbe495e90cedabc338d
- Size of remote file:
- 438 MB
- SHA256:
- 11c1fbfb7bfc34cbd315a86403796285773370993eec41e49eae205d5de5f3f5
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