Text Classification
jev-style
Safetensors
minicpm
minicpm5
system-one
decision-model
probability
calibration
agent
routing
Instructions to use link921/CPM-jev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- jev-style
How to use link921/CPM-jev with jev-style:
pip install "jev-style[torch]"
from jev_style import JevStyle, noul, choice js = JevStyle.from_pretrained("link921/CPM-jev") out = js.decide("I was charged twice for one order.", { "billing": noul("This message is about billing."), "team": choice("Which team should handle it?", ["billing", "shipping", "tech"]), }) print(out["answers"]["team"]["choice"]) - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from link921/CPM-jev: direct link, hf CLI and curl.
- Browser
- Download file 401 Bytes
-
https://huggingface.co/link921/CPM-jev/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://link921/CPM-jev/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/link921/CPM-jev/resolve/main/tokenizer_config.json
401 Bytes
| { | |
| "add_prefix_space": null, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "</s>", | |
| "legacy": true, | |
| "model_max_length": 524288, | |
| "pad_token": "</s>", | |
| "sp_model_kwargs": {}, | |
| "spaces_between_special_tokens": false, | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } | |