Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use selimsametoglu/selims with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selimsametoglu/selims with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selimsametoglu/selims")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selimsametoglu/selims") model = AutoModelForSequenceClassification.from_pretrained("selimsametoglu/selims", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from selimsametoglu/selims: direct link, hf CLI and curl.
- Browser
- Download file 670 MB
-
https://huggingface.co/selimsametoglu/selims/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://selimsametoglu/selims/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/selimsametoglu/selims/resolve/main/pytorch_model.bin
670 MB
- Xet hash:
- 753907b3600c2cd685fc0ce8495808349748e52b9fd0903b10f0c0f6e96381f1
- Size of remote file:
- 670 MB
- SHA256:
- 9cfcb11683fdc80e087e8f0886773a7c7e6d992a9ff8e97dbc9825f0323c471b
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