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 special_tokens_map.json from xysmalobia/sequence_classification: direct link, hf CLI and curl.
- Browser
- Download file 112 Bytes
-
https://huggingface.co/xysmalobia/sequence_classification/resolve/refs%2Fpr%2F3/special_tokens_map.json
- Command line
-
hf download hf://xysmalobia/sequence_classification@refs/pr/3/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/xysmalobia/sequence_classification/resolve/refs%2Fpr%2F3/special_tokens_map.json
112 Bytes
| {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"} |