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 training_args.bin from TieIncred/verizon_model1: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/TieIncred/verizon_model1/resolve/main/training_args.bin
- Command line
-
hf download hf://TieIncred/verizon_model1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/TieIncred/verizon_model1/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 810b386f97a6d13eb5d87b130ed1b72463d5be6bae85426c83459dea02ed9ac5
- Size of remote file:
- 3.45 kB
- SHA256:
- 5a16f5ee922ed700cd8ee091175e2eb9d4d2446a0a7dddb6a2d13d8df9a94639
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