Text Classification
Transformers
Safetensors
multilingual
modernbert
routing
llm-routing
prompt-classification
complexity-estimation
text-embeddings-inference
Instructions to use scombat/s1d1-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scombat/s1d1-router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scombat/s1d1-router")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scombat/s1d1-router") model = AutoModelForSequenceClassification.from_pretrained("scombat/s1d1-router", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download tutorials/04-codex.md from scombat/s1d1-router: direct link, hf CLI and curl.
- Browser
- Download file 1.5 kB
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https://huggingface.co/scombat/s1d1-router/resolve/main/tutorials/04-codex.md
- Command line
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hf download hf://scombat/s1d1-router/tutorials/04-codex.md
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curl -L -o 04-codex.md https://huggingface.co/scombat/s1d1-router/resolve/main/tutorials/04-codex.md
1.5 kB
| # Codex CLI | |
| Facts from the Codex configuration reference (2026-10-15): `config.toml` keys `model`, `model_provider`, | |
| `[model_providers.<id>]` (`base_url`, `env_key`, `wire_api`; `responses` is the only supported value), | |
| `model_reasoning_effort` (values depend on the model: `low`, `medium`, `high`, `xhigh`, …), profile files | |
| `$CODEX_HOME/<name>.config.toml` selected with `--profile`, and lifecycle hooks (`features.hooks = true`, event | |
| `UserPromptSubmit`, command handlers). I did not find a documented way for a hook to change the model. | |
| ## 1. Choose at launch (*router untested; `-m` and `-c` assumed from the Codex CLI*) | |
| ```bash | |
| python integrations/serve.py --model scombat/s1d1-router --policy integrations/policy.example.yaml & | |
| python integrations/routed.py codex "fix the failing test in utils/" | |
| ``` | |
| runs `codex -m <model> -c model_reasoning_effort="<effort>" "<prompt>"`. Edit the `codex` profile in | |
| `policy.example.yaml` first: put the model ids of your account in `models` (they are placeholders) and keep only the | |
| efforts your models accept. If `-c` is not available in your version, use profile files (one per tier) and | |
| `--profile`. | |
| ## 2. Through a gateway | |
| Point a custom provider at a LiteLLM proxy (`base_url = "http://localhost:4000/v1"`, `env_key`), with the Responses | |
| API enabled on the proxy, and use the hook of `02-litellm.md`. *Untested: the Responses path of the hook is not | |
| written; check that LiteLLM runs `async_pre_call_hook` on `/v1/responses` for your version.* | |