Text Classification
Transformers
Safetensors
modernbert
routing
llm-routing
prompt-classification
multilingual
text-embeddings-inference
Instructions to use scombat/s1d1-router-6src-compact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scombat/s1d1-router-6src-compact with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scombat/s1d1-router-6src-compact")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scombat/s1d1-router-6src-compact") model = AutoModelForSequenceClassification.from_pretrained("scombat/s1d1-router-6src-compact", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download variant.json from scombat/s1d1-router-6src-compact: direct link, hf CLI and curl.
- Browser
- Download file 294 Bytes
-
https://huggingface.co/scombat/s1d1-router-6src-compact/resolve/main/variant.json
- Command line
-
hf download hf://scombat/s1d1-router-6src-compact/variant.json
-
curl -L -o variant.json https://huggingface.co/scombat/s1d1-router-6src-compact/resolve/main/variant.json
294 Bytes
| { | |
| "backend": "torch", | |
| "recipe": "torch fp16", | |
| "source": "trained in this project (pipeline/05_train.py, pipeline/07_variants.py)", | |
| "parameters": 135708693, | |
| "sigma": 0.1062, | |
| "sigma_rows": 4850, | |
| "sigma_date": "2026-10-20", | |
| "max_length": 1024, | |
| "score_center": 0.5, | |
| "score_scale": 0.25 | |
| } | |