Instructions to use joelb/custom-handler-tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joelb/custom-handler-tutorial with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joelb/custom-handler-tutorial")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joelb/custom-handler-tutorial") model = AutoModelForSequenceClassification.from_pretrained("joelb/custom-handler-tutorial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from joelb/custom-handler-tutorial: direct link, hf CLI and curl.
- Browser
- Download file 112 Bytes
-
https://huggingface.co/joelb/custom-handler-tutorial/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://joelb/custom-handler-tutorial/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/joelb/custom-handler-tutorial/resolve/main/special_tokens_map.json
112 Bytes
| {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"} |