Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use joniponi/communication-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joniponi/communication-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joniponi/communication-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joniponi/communication-classifier") model = AutoModelForSequenceClassification.from_pretrained("joniponi/communication-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from joniponi/communication-classifier: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/joniponi/communication-classifier/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://joniponi/communication-classifier@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/joniponi/communication-classifier/resolve/refs%2Fpr%2F1/training_args.bin
3.06 kB
- Xet hash:
- efcbad09c193c42e7aacda6554c45678c66083bbb5e9724a308a9aaa291726fc
- Size of remote file:
- 3.06 kB
- SHA256:
- ddc45aa5bf55946c4ac254aad1fb0befa95ccaa5bf6cbfe9f2793624fe98bc7d
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