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@@ -24,7 +24,7 @@ The use of this model is governed by the [Llama 2 Community License Agreement](h
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Llama2-70B-SteerLM-Chat is a 70 billion parameter generative language model instruct-tuned using SteerLM technique. It takes input with context length up to 4,096 tokens.
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The model has been aligned using the SteerLM method developed by NVIDIA to allow for user control of model outputs (in creativity, complexity and verbosity) during inference while having simplified training compared to RLHF techniques.
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Llama2-70B-SteerLM-Chat reaches **7.54** on MT Bench, the highest among models trained on open-source datasets based on [MT Bench Leaderboard](https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard) as of 15 Nov 2023.
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Try this model instantly for free hosted by us at [NVIDIA AI Playground](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/models/llama2-70b-steerlm). You can use this in the provided UI or through a limited access API (up to 10, 000 requests within 30 days). If you would need more requests, we demonstrate how you can set up an inference server below.
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Llama2-70B-SteerLM-Chat is a 70 billion parameter generative language model instruct-tuned using SteerLM technique. It takes input with context length up to 4,096 tokens.
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The model has been aligned using the SteerLM method developed by NVIDIA to allow for user control of model outputs (in creativity, complexity and verbosity) during inference while having simplified training compared to RLHF techniques.
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Llama2-70B-SteerLM-Chat reaches **7.54** on MT Bench, the highest among **commercial-use-friendly** models trained on open-source datasets based on [MT Bench Leaderboard](https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard) as of 15 Nov 2023.
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Try this model instantly for free hosted by us at [NVIDIA AI Playground](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/models/llama2-70b-steerlm). You can use this in the provided UI or through a limited access API (up to 10, 000 requests within 30 days). If you would need more requests, we demonstrate how you can set up an inference server below.
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