Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use yangel88/text_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangel88/text_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yangel88/text_classification_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yangel88/text_classification_model") model = AutoModelForSequenceClassification.from_pretrained("yangel88/text_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from yangel88/text_classification_model: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/yangel88/text_classification_model/resolve/main/training_args.bin
- Command line
-
hf download hf://yangel88/text_classification_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/yangel88/text_classification_model/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 820fc510323c95c547faeb32849924883fbdb43a984860d041ebe3e8b8c403e0
- Size of remote file:
- 4.03 kB
- SHA256:
- 0c6885ab295cafdcb9f91eece494b57331678b401d003f14d05877ab03d27d64
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