Feature Extraction
Transformers
Safetensors
Korean
sysone
decision-model
classification
router
korean
custom_code
Instructions to use leapshared/nari-router-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leapshared/nari-router-4b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="leapshared/nari-router-4b", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("leapshared/nari-router-4b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
nari-router-4b: nari-decision-4b v3.2 + 우리 말 LoRA(합침), 씨앗 1 · 3에포크 · lm_weight 0.5 · 온도 1.86
5451004 verified Download tokenizer.json from leapshared/nari-router-4b: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/leapshared/nari-router-4b/resolve/main/tokenizer.json
- Command line
-
hf download hf://leapshared/nari-router-4b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/leapshared/nari-router-4b/resolve/main/tokenizer.json
20 MB
- Xet hash:
- e558cdad9a88d177076f9525ed4ef2d55dfd5dafafd6baac7c6105590ab49b7b
- Size of remote file:
- 20 MB
- SHA256:
- a5cd9732badce41de57e6efce8302930ded1c1188c5f81feb2bd6c24c4a1941f
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