Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,39 @@
+---
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+  - mixture-of-experts
+  - moe
+  - corm
+---
+
+# CoRM
+
+Checkpoints for the paper [Beyond Magnitude: Contrastive Routing for Modular Mixture-of-Experts](https://arxiv.org/abs/2609.01100).
+
+| Model | Active Params | Total Params | Routing | Link |
+|---|---|---|---|---|
+| CoRM-182M | 182M | 777M | Top-1 | [link](https://huggingface.co/ilsp/CoRM-182M-top1) |
+| CoRM-182M | 266M | 777M | Top-2 | [link](https://huggingface.co/ilsp/CoRM-182M-top2) |
+| CoRM-469M | 469M | 2.58B | Top-1 | [link](https://huggingface.co/ilsp/CoRM-469M-top1) |
+
+## Usage
+
+These models use custom modeling code, so `trust_remote_code=True` is required.
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "ilsp/CoRM-182M-top1"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)
+
+inputs = tokenizer("The capital of Greece is", return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=32)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Citation
+
+<!-- TODO: add BibTeX. -->