Instructions to use p1atdev/multi-tokenizers-processor-sample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use p1atdev/multi-tokenizers-processor-sample with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("p1atdev/multi-tokenizers-processor-sample", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from p1atdev/multi-tokenizers-processor-sample: direct link, hf CLI and curl.
- Browser
- Download file 173 Bytes
-
https://huggingface.co/p1atdev/multi-tokenizers-processor-sample/resolve/b5e658db7e5ff928e127d2af5d5252b88987bb89/processor_config.json
- Command line
-
hf download hf://p1atdev/multi-tokenizers-processor-sample@b5e658db7e5ff928e127d2af5d5252b88987bb89/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/p1atdev/multi-tokenizers-processor-sample/resolve/b5e658db7e5ff928e127d2af5d5252b88987bb89/processor_config.json
173 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": [ | |
| "processor_multitokenizers.MultiTokenizersProcessor", | |
| null | |
| ] | |
| }, | |
| "processor_class": "MultiTokenizersProcessor" | |
| } | |