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 training_args.bin from pa-shk/postcard_multilabel_classifier: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/pa-shk/postcard_multilabel_classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://pa-shk/postcard_multilabel_classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pa-shk/postcard_multilabel_classifier/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- ceaa8b17427d47bba5f096eb67684f4076de5606806a17ff59ee8fabff7a3429
- Size of remote file:
- 3.64 kB
- SHA256:
- 6421acd27c36ac7ac33091a3d5d55d8c23e64a8e47e5d514afa4393caa249f59
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