Text Classification
Transformers
PyTorch
TensorFlow
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use TirkNork/sentence_classfication_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TirkNork/sentence_classfication_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TirkNork/sentence_classfication_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TirkNork/sentence_classfication_test") model = AutoModelForSequenceClassification.from_pretrained("TirkNork/sentence_classfication_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TirkNork/sentence_classfication_test: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/TirkNork/sentence_classfication_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TirkNork/sentence_classfication_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TirkNork/sentence_classfication_test/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 9f37036718ecd65d8900c09ee0ad65d0ef105726ef3a437a762d2c29503ac3a1
- Size of remote file:
- 268 MB
- SHA256:
- 694f05e9e48c3eddc5da4e2af99f0dc388692781184e9b8fd6246234beabe8e3
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