Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
text-embeddings-inference
Instructions to use afg1/sentence_contraditcion_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afg1/sentence_contraditcion_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="afg1/sentence_contraditcion_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("afg1/sentence_contraditcion_model") model = AutoModelForSequenceClassification.from_pretrained("afg1/sentence_contraditcion_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from afg1/sentence_contraditcion_model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/afg1/sentence_contraditcion_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://afg1/sentence_contraditcion_model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/afg1/sentence_contraditcion_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
268 MB
- Xet hash:
- cbda36fcc14de638af2c427f9b1bea28126eb24f64e2d6f295251c3a154f845d
- Size of remote file:
- 268 MB
- SHA256:
- b3feb795f4ea6d06596737a8a13f9ce1ab0a567add97f861410fa5d73dc5e212
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