Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use xysmalobia/sequence_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xysmalobia/sequence_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xysmalobia/sequence_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xysmalobia/sequence_classification") model = AutoModelForSequenceClassification.from_pretrained("xysmalobia/sequence_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from xysmalobia/sequence_classification: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/xysmalobia/sequence_classification/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://xysmalobia/sequence_classification@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/xysmalobia/sequence_classification/resolve/refs%2Fpr%2F1/training_args.bin
2.86 kB
- Xet hash:
- 874a7132ac873e3f6de61ff5cff037974e7ee3f818fbd3e8dec08d6df554d0c6
- Size of remote file:
- 2.86 kB
- SHA256:
- af39ab08ea2b0d4528ed4b14049d67056f09b99f140ef650525977b8326a76f0
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