Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use GioReg/bertNEGsentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GioReg/bertNEGsentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GioReg/bertNEGsentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GioReg/bertNEGsentiment") model = AutoModelForSequenceClassification.from_pretrained("GioReg/bertNEGsentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from GioReg/bertNEGsentiment: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/GioReg/bertNEGsentiment/resolve/main/training_args.bin
- Command line
-
hf download hf://GioReg/bertNEGsentiment/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/GioReg/bertNEGsentiment/resolve/main/training_args.bin
3.18 kB
- Xet hash:
- dcbfa3626e41b037777130d2af9f4cadaf6aa6bcb8d4544ea5588cf351efde41
- Size of remote file:
- 3.18 kB
- SHA256:
- c46830aca2e41507f2288e43f6edc63b0c3208f093f4fb100eec148641e93679
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