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Create model-support.md for NeMoRL #1705

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28 changes: 28 additions & 0 deletions docs/about/model-support.md
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# Model Support

## Broad coverage for 🤗Hugging Face models via [NeMo AutoModel](https://github.com/NVIDIA-NeMo/Automodel)

NeMo-RL support 🤗Hugging Face models from the following classes
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⚠️ Potential issue | 🟡 Minor

Fix grammatical error: "support" should be "supports".

Line 5 is missing the verb conjugation.

-NeMo-RL support 🤗Hugging Face models from the following classes
+NeMo-RL supports 🤗Hugging Face models from the following classes
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

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NeMo-RL support 🤗Hugging Face models from the following classes
NeMo-RL supports 🤗Hugging Face models from the following classes
🤖 Prompt for AI Agents 
In docs/about/model-support.md around line 5, the sentence "NeMo-RL support
🤗Hugging Face models from the following classes" uses incorrect verb
conjugation; change "support" to "supports" so the sentence reads "NeMo-RL
supports 🤗Hugging Face models from the following classes."

- LLMs ([AutoModelForCausalLM](https://huggingface.co/docs/transformers/en/model_doc/auto#transformers.AutoModelForCausalLM))
- VLMs ([AutoModelForImageTextToText](https://huggingface.co/docs/transformers/en/model_doc/auto#transformers.AutoModelForImageTextToText))

for model sizes under 70B at up to 32k sequence length.

## Optimal acceleration for top models via [NeMo Megatron-bridge](https://github.com/NVIDIA-NeMo/Megatron-Bridge)

[NeMo Megatron-bridge](https://github.com/NVIDIA-NeMo/Megatron-Bridge) provides acceleration [recipes](https://github.com/NVIDIA-NeMo/RL/tree/main/examples/configs/recipes) for the below models. Users can also leverage the on-line checkpoint conversion (i.e the "bridge") by directly inputting a 🤗Hugging Face checkpoint.

LLMs:
- Qwen: Qwen2.5-1.5B/7B/32B, Qwen3-1.5B/8B/32B, Qwen3-30B-A3B, Qwen3-235B-A22B
- Llama: Llama 3.1/3.3-8B, Llama 3.1/3.3-70B, Llama 3.2-1B
- Deepseek: Deepseek-V3/R1-671B
- Mistral: Mistral-NeMo-12B
- Moonlight-16B-A3B
- Gemma: Gemma-3-1B/27B
- GPT-OSS: GPT-OSS-20B/120B
- NeMotron: Llama-Nemotron-Super-49B, Nemotron-nano-v2-12B, Nemotron-Nano-v3-30A3B

VLMs:
- Qwen: Qwen2.5VL-3B

In addition, please refer to our [performance page](https://docs.nvidia.com/nemo/rl/latest/about/performance-summary.html) for benchmarks and full reproducible scripts
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