Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use wenkai-li/new_classifer_epoch7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wenkai-li/new_classifer_epoch7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wenkai-li/new_classifer_epoch7")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wenkai-li/new_classifer_epoch7") model = AutoModelForSequenceClassification.from_pretrained("wenkai-li/new_classifer_epoch7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from wenkai-li/new_classifer_epoch7: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/wenkai-li/new_classifer_epoch7/resolve/main/training_args.bin
- Command line
-
hf download hf://wenkai-li/new_classifer_epoch7/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/wenkai-li/new_classifer_epoch7/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 76dac3efaa550f266a116b9da0fc97d8acf70fb245f5b37298d81cca6162ec1d
- Size of remote file:
- 3.38 kB
- SHA256:
- 9146400e2d4b6d9a95b0997c36f3a083bf6886edbe20c040cbd8fc3e19a34055
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