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
File size: 1,496 Bytes
7783834 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | # 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.*
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