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 pytorch_model.bin from GioReg/bertNEGsentiment: direct link, hf CLI and curl.
- Browser
- Download file 737 MB
-
https://huggingface.co/GioReg/bertNEGsentiment/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://GioReg/bertNEGsentiment/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/GioReg/bertNEGsentiment/resolve/main/pytorch_model.bin
737 MB
- Xet hash:
- e5342842c75944758bb26de1c9d9c2ee161eee0d99e3337db2833eb0a2fc418e
- Size of remote file:
- 737 MB
- SHA256:
- 81db1551e41ebdfe7b362bbad9beae80ebd03972dc90dcea402e0ea74a0b41fa
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