Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
Russian
distilbert
text-embeddings-inference
Instructions to use pa-shk/postcard_multilabel_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pa-shk/postcard_multilabel_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pa-shk/postcard_multilabel_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pa-shk/postcard_multilabel_classifier") model = AutoModelForSequenceClassification.from_pretrained("pa-shk/postcard_multilabel_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pa-shk/postcard_multilabel_classifier: direct link, hf CLI and curl.
- Browser
- Download file 41.5 MB
-
https://huggingface.co/pa-shk/postcard_multilabel_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://pa-shk/postcard_multilabel_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pa-shk/postcard_multilabel_classifier/resolve/main/pytorch_model.bin
41.5 MB
- Xet hash:
- a9763437f4531b2920d03fb4004a0357a4dae8ac9d6f2c466849b65410dcbd0b
- Size of remote file:
- 41.5 MB
- SHA256:
- 2552cf3fc16ab6cb5629b24dd7aa5dbffaaa07f8ef990d62344a322c05805132
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