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GPTJForCausalLM Support (#7839)

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Co-authored-by: b8zhong <b8zhong@uwaterloo.ca>
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Wenchen Lo
2026-01-29 21:00:04 -08:00
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co-authored by b8zhong
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@@ -58,6 +58,7 @@ in the GitHub search bar.
| **Ling** (16.8B–290B) | `inclusionAI/Ling-lite`, `inclusionAI/Ling-plus` | InclusionAI’s open MoE models. Ling-Lite has 16.8B total / 2.75B active parameters, and Ling-Plus has 290B total / 28.8B active parameters. They are designed for high performance on NLP and complex reasoning tasks. |
| **Granite 3.0, 3.1** (IBM) | `ibm-granite/granite-3.1-8b-instruct` | IBM's open dense foundation models optimized for reasoning, code, and business AI use cases. Integrated with Red Hat and watsonx systems. |
| **Granite 3.0 MoE** (IBM) | `ibm-granite/granite-3.0-3b-a800m-instruct` | IBM’s Mixture-of-Experts models offering strong performance with cost-efficiency. MoE expert routing designed for enterprise deployment at scale. |
| **GPT-J** (6B) | `EleutherAI/gpt-j-6b` | EleutherAI's GPT-2-like causal language model (6B) trained on the [Pile](https://pile.eleuther.ai/) dataset. |
| **Orion** (14B) | `OrionStarAI/Orion-14B-Base` | A series of open-source multilingual large language models by OrionStarAI, pretrained on a 2.5T token multilingual corpus including Chinese, English, Japanese, Korean, etc, and it exhibits superior performance in these languages. |
| **Llama Nemotron Super** (v1, v1.5, NVIDIA) | `nvidia/Llama-3_3-Nemotron-Super-49B-v1`, `nvidia/Llama-3_3-Nemotron-Super-49B-v1_5` | The [NVIDIA Nemotron](https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/) family of multimodal models provides state-of-the-art reasoning models specifically designed for enterprise-ready AI agents. |
| **Llama Nemotron Ultra** (v1, NVIDIA) | `nvidia/Llama-3_1-Nemotron-Ultra-253B-v1` | The [NVIDIA Nemotron](https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/) family of multimodal models provides state-of-the-art reasoning models specifically designed for enterprise-ready AI agents. |